Artificial Intelligence (AI) Engineer, Video Analytics, Onsite in Charlotte, NC
The Artificial Intelligence (AI) Engineer, Video Analytics will work with a team that builds GPU‑accelerated video analytics for real‑time safety monitoring across large fleets and industrial environments. The system processes high‑volume video streams, runs YOLO‑based detection models, performs temporal tracking and smoothing to reduce false positives, and identifies actionable safety violations. Inference results are published to downstream APIs and integrated with Azure Event Hub, Blob Storage, and cloud monitoring systems. If you enjoy pushing GPU performance limits, crafting resilient Machine Learning (ML) pipelines, and building real‑world safety applications that make an impact, you will fit right in. This position is 100% Onsite in Charlotte, NC.
Artificial Intelligence (AI) Engineer Responsibilities:
- Develop and optimize GPU‑accelerated video inference pipelines, including batching, stride control, and throughput tuning.
- Implement, evaluate, and improve object detection models (YOLO or similar) and build temporal smoothing/tracking logic for safety event detection.
- Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools to maximize throughput and minimize latency/VRAM usage.
- Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services.
- Add robust metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs.
- Collaborate on dataset curation, labeling, model training, validation, and experiment tracking.
- Support containerized deployments (Docker) and assist with monitoring and scaling production workloads.
QualificationsArtificial Intelligence (AI) Engineer Qualifications:
- 3+ years of experience shipping computer vision or machine learning systems to production.
- Strong proficiency in Python and experience with OpenCV, PyTorch, async I/O frameworks, and API integrations.
- Hands-on experience with YOLO/Ultralytics or similar object detection frameworks.
- Solid understanding of video processing fundamentals: frame sampling, temporal filtering, confidence thresholds, and multi-camera aggregation.
- Experience optimizing GPU inference performance batching, stride, TensorRT, CUDA, model quantization, and throughput tuning.
- Experience with Azure Event Hub, Blob Storage, Application Insights, or similar cloud messaging/storage platforms is a plus.
- Familiarity with Docker, cloud deployments, and production monitoring systems is a plus.
- Experience in temporal/sequence analysis for event detection is a plus.
- Background in video analytics for safety, compliance, or industrial/transportation environments is a plus.
- Tech Stack: aiohttp, Application Insights, asyncio, Azure Blob Storage, Azure Event Hub, CUDA, Docker, gRPC, ML - Machine Learning, ONNX, OpenCV, Python, PyTorch, RESTful APIs, Telemetry Tools, TensorRT, and Ultralytics YOLO.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: Charlotte NC Jobs, Artificial Intelligence (AI) Engineer, aiohttp, Application Insights, asyncio, Azure Blob Storage, Azure Event Hub, CUDA, Docker, gRPC, ML, Machine Learning, ONNX, OpenCV, Python, PyTorch, RESTful APIs, Telemetry Tools, TensorRT, and Ultralytics YOLO, Video Analytics, North Carolina Recruiters, IT Jobs, North Carolina Recruiting
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Read LessAccount Manager, Onsite in Charlotte, NC
The Account Manager is responsible for coordinating client-facing activities and internal delivery efforts to ensure the successful execution of client projects and ongoing account operations. This role serves as a primary point of contact for assigned clients, manages project planning and tracking, supports new client on-boarding, and ensures alignment between client needs, internal teams, and delivered solutions. The Account Manager plays a critical role in maintaining strong client relationships, managing account health, and ensuring development, deployment, hardware fulfillment, and support activities are executed efficiently and transparently. This position is 100% Onsite in Charlotte, NC.
Account Manager Responsibilities:
Client Communication, Account Management & Coordination
- Serve as the primary Account Manager and main point of contact for assigned clients and owning the overall client relationship.
- Maintain active communication with clients regarding open items, including development, planning, escalations, device fulfillment, and hardware installations.
- Follow up on pending items and provide regular status updates to clients.
- Proactively monitor account health, identify risks or dependencies, and communicate potential impacts to scope, timeline, or delivery.
- Ensure clients are informed of any development work or operational changes associated with their account.
New Client On-boarding
- Manage and coordinate the on-boarding of new clients, including kickoff meetings, requirement validation, timeline alignment, and internal handoffs.
- Partner with Product, Development, Sales, Support, and Learning & Development teams to ensure a smooth onboarding and post-go-live transition.
Project Planning & Tracking
- Create and maintain project plans for client initiatives and on-boarding efforts.
- Track project progress through completion, ensuring visibility into milestones and deliverables.
- Track all development work associated with client projects and accounts.
- Participate in scrum ceremonies, including planning sessions and reviews, to stay aligned with delivery efforts.
Requirements & Delivery Alignment
- Gather requirements directly from clients and communicate them clearly to product and development teams.
- Follow up internally on client requests to ensure timely progress and resolution.
- Review support tickets and coordinate with Support and Learning & Development supervisors when additional alignment or escalation is required.
Hardware Order Requests & Deployment Management
- Coordinate and manage hardware order requests, including device fulfillment, inventory coordination, shipping, and tracking.
- Schedule and oversee hardware installations and deployments, ensuring readiness and clear communication with clients and internal teams.
- Schedule and coordinate deployment notifications for clients.
- Complete all preparation activities required for successful deployments.
- Create and distribute clear and accurate release notes for client-facing deployments.
Industry Awareness & Product Knowledge
- Maintain awareness of industry trends, client use cases, and evolving needs related to supported products.
- Develop and maintain strong working knowledge of the products used by clients.
- Review and analyze product analytics to confirm usage patterns, adoption, and trends.
- Identify potential risks, optimization opportunities, or gaps in product usage and communicate findings to internal teams.
- Use insights from analytics and client behavior to proactively support planning, product improvements, and client discussions.
QualificationsAccount Manager Qualifications:
Education & Experience
- Minimum of 5 years of experience in Project Management, Account Management, or an equivalent professional background.
- Demonstrated experience managing client-facing projects and accounts within a software, technology, or IT solutions environment.
- Experience supporting client onboarding, hardware logistics, and deployment coordination.
- Proven experience planning, tracking, and delivering complex initiatives in a fast-paced, deadline-driven environment.
Skills & Competencies
- Strong understanding of business and client needs with the ability to coordinate across technical and non-technical teams.
- Proven experience working in agile and scrum-based delivery environments.
- Excellent organizational and prioritization skills with the ability to manage multiple clients, initiatives, and competing demands.
- Strong analytical skills with the ability to review data, identify trends, risks, and opportunities, and communicate findings clearly.
Exceptional written and verbal communication skills, including the ability to communicate status, risks, and technical concepts to non-technical audiences.
- Detail-oriented, deadline-driven, and able to perform well under pressure.
- Proficient in Microsoft Office (Excel, Word, Outlook, Project) and Jira; SharePoint experience preferred.
- Self-starter with strong follow-through and a professional, client-focused attitude.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: Charlotte NC Jobs, Account Manager, Account Management, Logistics, Microsoft Office, Project Management, Project Manager, Sales, North Carolina Recruiters, IT Jobs, North Carolina Recruiting
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Read LessStaff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As the Staff Machine Learning Engineer, you own the execution layer of intelligence. You translate research direction into reliable, scalable, production-grade Machine Learning (ML) systems. This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints. This position is 100% Remote.
Staff Machine Learning Engineer Responsibilities:
- Own end-to-end Machine Learning (ML) system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- Design and maintain data systems for high-quality synthetic and real-world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate Machine Learning (ML) systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety
Staff Machine Learning Engineer Outcomes
- Research and models reliably translate into production-ready solutions with clear performance and quality targets.
- Machine Learning (ML) pipelines, training loops, and inference systems are stable, efficient, and maintainable.
- Production issues are detected, debugged, and resolved quickly, minimizing user impact.
- Team members are supported, aligned, and able to deliver high-impact Machine Learning (ML) work with minimal friction.
- Iterations on models and systems are measurable, safe, and improve user experience over time.
QualificationsStaff Machine Learning Engineer Qualifications:
- Experience building or shipping real Machine Learning (ML) systems used by people, not just demos.
- Artificial Intelligence (AI) experience required.
- Experience working with large models and understanding their failure modes.
- Experience writing strong, production-grade code.
- You are self-directed, pragmatic, and take full ownership of outcomes.
- Experience communicating clearly and collaborate well in small, high-trust teams.
- Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Staff Machine Learning Engineer, Data Pipelines, DPO, GPU, JAX, LoRA, Machine Learning Engineer, ML, Machine Learning, Python, PyTorch, QLoRA, SFT, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Read LessSoftware Engineer, Desktop, Artificial Intelligence (AI) Required, Work From Home
The Software Engineer, Desktop will own how the system behaves on desktop environments. Your work focuses on reliability, performance, and real-time behavior in production desktop applications. This position is 100% Remote.
Software Engineer, Desktop Responsibilities:
- Build and maintain cross-platform desktop applications using Electron.
- Design responsive and scalable UIs for real-time collaboration.
- Implement desktop-specific functionality including file system access, native notifications, auto-updates, and deep linking.
- Integrate Artificial Intelligence (AI)-powered features (chat, agents, Artificial Intelligence (AI) assistance) via backend APIs.
- Optimize startup time, memory usage, and runtime performance.
- Profile and reduce Electron overhead.
- Manage large local state and message history efficiently.
- Ensure smooth real-time updates (messages, typing indicators, presence).
- Maintain stability across macOS and Windows environments.
QualificationsSoftware Engineer, Desktop Qualifications:
- Proven software engineering experience.
- Artificial Intelligence (AI) experience required.
- Hands-on experience building production Electron applications.
- Strong proficiency in JavaScript and TypeScript.
- Experience with React or similar UI frameworks.
- Solid understanding of the desktop application lifecycle.
- Experience with IPC communication.
- Experience working with local storage (SQLite, IndexedDB, filesystem).
- Experience with WebSockets or other real-time transport mechanisms.
- Strong debugging and performance profiling skills.
- Familiarity with native OS behaviors on macOS or Windows.
- Tech Stack: Electron, Node.js, NoSQL, SQL, and Typescript.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Software Engineer, Desktop, AI, API, Artificial Intelligence, Electron, IndexedDB, IPC Communications, JavaScript, macOS, Node.js, NoSQL, React, Real Time, SQL, SQLite, Typescript, UI, User Interface, WebSockets, Windows, Software Engineer, Software Developer, Programming, Programmer Analyst, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Read LessSenior Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As the Senior Machine Learning Engineer, you are an independent owner of critical Machine Learning (ML) subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale. This is a hands-on, high-impact role focused on depth. This position is 100% Remote.
Senior Machine Learning Engineer Responsibilities:
- Build core Machine Learning (ML) systems that power a proactive, long-horizon Artificial Intelligence (AI) product.
- Own work end-to-end: data preparation, training, evaluation, inference, and iteration.
- Turn research ideas into working systems that run reliably in production.
- Debug model failures and system issues using real production signals.
- Iterate quickly: ship, measure outcomes, refine, and repeat.
- Collaborate closely with research, product, and engineering to deliver real user impact.
- Mentor and review work from other Machine Learning (ML) engineers through example and technical judgment.
- Work under real production constraints: latency, cost, reliability, and safety
Senior Machine Learning Engineer Outcomes:
- Machine Learning (ML) models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets.
- Complex production issues are monitored, debugged, and resolved with minimal disruption.
- Training, inference, and data pipelines are robust, scalable, and maintainable over time.
- Drive measurable improvements in Machine Learning (ML) systems based on real-world signals and user feedback.
- Provide mentorship and technical guidance to peers, raising the overall ML engineering standard.
- Collaborate cross-functionally to ensure Machine Learning (ML) features integrate seamlessly into products and meet business goals.
QualificationsSenior Machine Learning Engineer Qualifications:
- Experience building and shipping Machine Learning (ML) systems used by real users.
- Artificial Intelligence (AI) experience required.
- Experience understanding how modern Machine Learning (ML) models behave and misbehave in production.
- Experience writing strong, production-quality code and think in systems, not scripts.
- Experience taking ownership, work independently, and push work across the finish line.
- You learn fast, communicate clearly, and improve through iteration.
- Tech Stack: GPU-based training and inference systems, JAX, Python, and PyTorch.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Senior Machine Learning Engineer, AI, Artificial Intelligence, Engineering, GPU, JAX, Machine Learning, Python, PyTorch, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Read LessMachine Learning Technical Lead, Artificial Intelligence (AI) Required, Work From Home
As Machine Learning Technical Lead, you own the execution layer of intelligence. You will translate research direction into reliable, scalable, production-grade ML systems. This role sits at the intersection of research, infrastructure, and product. You will be responsible for making models trainable, deployable, observable, and performant under real-world constraints. This position is 100% Remote.
Machine Learning Technical Lead Responsibilities:
- Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- Design and maintain data systems for high-quality synthetic and real-world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety
Machine Learning Technical Lead Outcomes:
- Research and models reliably translate into production-ready solutions with clear performance and quality targets.
- ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.
- Production issues are detected, debugged, and resolved quickly, minimizing user impact.
- Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.
- Iterations on models and systems are measurable, safe, and improve user experience over time.
QualificationsMachine Learning Technical Lead Qualifications:
- Experience building or shipping real Machine Learning systems used by people, not just demos.
- Artificial Intelligence (AI) experience required.
- Experience working with large models and understanding their failure modes.
- Experience writing strong, production-grade code.
- You are self-directed, pragmatic, and take full ownership of outcomes.
- You communicate clearly and collaborate well in small, high-trust teams.
- Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Machine Learning Technical Lead, AI, Artificial Intelligence, Distillation, DPO, GPU Optimization, JAX, LoRA, Machine Learning, Python, PyTorch, QLoRA, SFT, Technical Lead, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Read LessSenior Engineer, Internal Tools, Artificial Intelligence (AI) Required, Work From Home
The Senior AI Engineer is the engineering backbone of the internal tools team. Building and maintaining the platforms that every team in the company relies on. Your work directly increases organizational efficiency and enables teams to move faster. The Senior AI Engineer will own systems end-to-end, from scoping and architecture through production deployment and iteration, connecting multiple business systems into a seamless, reliable internal ecosystem. This position is 100% Remote.
Senior Engineer Responsibilities:
Build & Ship:
- Design, build, and maintain internal platforms and tools that serve People, Finance, Ops, Sales, and Engineering teams.
- Own features, end-to-end requirements, architecture, implementation, testing, deployment, and monitoring.
- Write clean, well-tested, production-grade code. You hold yourself to the same bar as customer-facing products.
Architecture & Integration:
- Build API-first integrations across the internal ecosystem connecting HRIS, CRM, finance platforms, knowledge management, and developer tools into a coherent stack.
- Design for reliability, performance, and scale what you build today must hold as the company grows 5–10x.
- Eliminate data silos. Build clean data pipelines that maintain a single source of truth across systems.
- Own your services in production: monitoring, alerting, incident response, and post-mortems.
AI & Automation:
- Build AI/LLM-powered features into internal workflows, automating approvals, knowledge retrieval, reporting, content generation, and operational processes.
- Move fast from prototype to production. You know the difference between a demo and a system that works at scale.
- Stay current on emerging AI capabilities and proactively identify where they unlock step-change improvements in internal productivity.
Collaboration & Influence:
- Work directly with business stakeholders to understand pain points and translate them into technical solutions. You don’t wait for a spec you help shape it.
- Pair with and mentor junior engineers. Raise the technical bar through code reviews, design reviews, and leading by example.
- Influence technical direction: propose architectural improvements, challenge assumptions, and drive best practices across the team.
QualificationsSenior Engineer Qualifications:
- 5+ years of professional software engineering experience, with meaningful time spent building internal tools, platforms, or business systems.
- Artificial Intelligence (AI) experience required.
- Strong full-stack or backend engineering skills. Proficient in at least one of: Python, Go, TypeScript/Node.js, or Java.
- Solid understanding of Cloud Infrastructure (GCP/AWS/Azure), Containerization (Docker/Kubernetes), CI/CD Pipelines, and modern DevOps practices.
- Hands-on experience building and maintaining API integrations between third-party SaaS platforms (e.g., Workday, Salesforce, Slack, NetSuite).
- Strong data fundamentals: relational databases, data modelling, ETL/ELT pipelines, and working knowledge of SQL.
- Comfort with ambiguity. You can take a vague business problem, break it down, and deliver a working solution without heavy handholding.
- Clear communicator who can explain technical tradeoffs to non-technical stakeholders.
- Experience with workflow orchestration tools (Temporal, Airflow, Prefect) or integration platforms (Workato, Tray.io, MuleSoft) is a plus.
- Frontend experience with React, Next.js, or equivalent modern frameworks is a plus.
- Familiarity with HRIS, ERP, or people systems data models and processes is a plus.
- Experience at a high-growth or AI-native company is a plus.
- Contributions to developer experience tooling, CLIs, or internal SDKs is a plus.
- Experience building or integrating AI/LLM-powered features not just experimenting, but shipping to real users is a plus.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Senior Engineer, AI, API, Artificial Intelligence, AWS, Azure, Backend, CI/CD Pipelines, Cloud Infrastructure, Containerization, CRM, DevOps, Docker, ETL, Full Stack, GCP, Go, Google Cloud Platform, HRIS, Java, Kubernetes, LLM, NetSuite, Node.js, Python, SaaS, Salesforce, Slack, Software as a Service, SQL, TypeScript, Workday, Programming, Programmer Analyst, Software Engineer, Software Developer, Work From Home, California Recruiters, IT Jobs, California Recruiting
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Read LessPrincipal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands-on, high-impact role focused on depth. This position is 100% Remote.
Principal Machine Learning Engineer Responsibilities:
- Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment.
- Design reproducible, high-performance training pipelines across GPU infrastructure.
- Architect inference systems that balance latency, throughput, cost, and reliability at scale.
- Design and maintain data systems for high-quality synthetic and real-world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety
Principal Machine Learning Engineer Outcomes:
- ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets.
- Models deployed to production achieve measurable quality improvements and meet user-impact goals.
- Production issues are proactively monitored, debugged, and resolved with clear root-cause analysis.
- Team and cross-functional collaborators benefit from clear guidance, best practices, and scalable ML solutions.
- Research-to-production cycles are efficient, safe, and continuously improve the product experience.
QualificationsPrincipal Machine Learning Engineer Qualifications:
- Strong background in deep learning and transformer-based architectures.
- Artificial Intelligence (AI) experience required.
- Hands-on experience training, fine-tuning, or deploying large-scale ML models in production.
- Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly.
- Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray).
- Strong software engineering fundamentals; you write robust, maintainable, production-grade systems.
- Experience with GPU optimization, including memory efficiency, quantization, and mixed precision.
- Comfort owning ambiguous, zero-to-one ML systems end-to-end.
- A bias toward shipping, learning fast, and improving systems through iteration.
- Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer.
- Contributions to open-source ML or systems libraries.
- Background in scientific computing, compilers, or GPU kernels.
- Experience with RLHF pipelines (PPO, DPO, ORPO).
- Experience training or deploying multimodal or diffusion models.
- Experience with large-scale data processing (Apache Arrow, Spark, Ray).
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Principal Machine Learning Engineer, Apache Arrow, DeepSpeed, DPO, FasterTransformer, FSDP, GPU Kernels, JAX, LLM, Machine Learning, Megatron, ML, ORPO, PPO, Principal Machine Learning Engineer, Pytorch, RLHF Pipelines, Spark, TensorRT-LLM, Virtual Large Language Model, vLLM, Work From Home, ZeRO Ray, California Recruiters, IT Jobs, California Recruiting
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Read LessMember of Technical Staff, Machine Learning, Artificial Intelligence (AI) Required, Work From Home
As a Member of Technical Staff, Machine Learning, you will build core ML components. The Member of Technical Staff will work on real production systems from day one, learning how large-scale ML behaves outside of research settings. The Member of Technical Staff role is for engineers who want to develop strong systems judgment by shipping, debugging, and iterating on real-world ML. This position is 100% Remote.
Member of Technical Staff Responsibilities:
- Build and improve ML components across data, training, evaluation, and inference.
- Fine-tune and adapt models as part of larger production systems.
- Implement evaluation and testing to understand model behavior.
- Help build and maintain data pipelines for real-world and synthetic data.
- Debug model issues, performance problems, and production incidents.
- Ship improvements iteratively and learn from real user feedback.
- Work closely with senior ML engineers and product teams.
- Work under real production constraints: latency, cost, reliability, and safety
Member of Technical Staff Outcomes:
- ML models in production meet expected accuracy, latency, and reliability targets.
- Production issues are identified quickly, debugged effectively, and root causes addressed.
- Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.
- Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.
- Iterations on models and systems are driven by real-world signals and measurable improvements.
QualificationsMember of Technical Staff Qualifications:
- Strong foundations in machine learning and modern neural architectures.
- Artificial Intelligence (AI) experience required.
- Some hands-on experience training, fine-tuning, or deploying ML models.
- Comfortable writing production-quality code and learning new tools quickly.
- Curious, coachable, and eager to learn from real systems in production.
- Able to work through ambiguity with guidance and grow ownership over time.
- Bias toward shipping, iteration, and continuous improvement.
- Tech Stack: GPU, JAX, ML, Machine Learning, Python, and PyTorch.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Member of Technical Staff, GPU, JAX, Machine Learning, Member of Technical Staff, ML, Python, PyTorch, Programming, Programmer Analyst, Software Engineer, Software Developer, Work From Home, California Recruiters, IT Jobs, California Recruiting
Looking to hire a Member of Technical Staff in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help.
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Read LessFull Stack Engineer, AI Systems, Artificial Intelligence (AI) Required, Work From Home
We are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users. This position is 100% Remote.
Full Stack Engineer Responsibilities:
- Build end-to-end product features across frontend, backend, and AI integrations.
- Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps.
- Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions.
- Design real-time AI interactions with streaming, partial results, and tight latency constraints.
- Improve system reliability, observability, and fallback mechanisms.
- Collaborate closely with ML, backend, and product teams to ship features end-to-end.
- Continuously iterate based on real usage and failure modes.
Full Stack Engineer Outcomes:
- Own and ship AI-native product features that move beyond chat into persistent, goal-driven workflows.
- Design and deploy agent workflows that reliably complete multi-step tasks across tools and sessions.
- Reduce latency and improve responsiveness of AI interactions while maintaining output quality.
- Build robust fallback and recovery mechanisms for LLM and tool failures in production environments.
- Improve the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoring.
- Establish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systems.
- Contribute to a product experience where AI feels proactive, consistent, and dependable over time.
QualificationsFull Stack Engineer Qualifications:
- Strong experience in Full Stack Engineering (Frontend and Backend).
- Artificial Intelligence (AI) experience required.
- Solid understanding of system design and API architecture.
- Experience working with LLMs, RAG systems, or AI-powered applications.
- Ability to handle ambiguity and make pragmatic engineering decisions.
- Strong ownership; able to take features from idea to production.
- Comfort working in fast-moving environments with evolving requirements.
- Tech Stack: AI, Anthropic, API, Artificial Intelligence, Backend, Docker, Frontend, Kubernetes, Next.js, Node.js, NoSQL, OpenAI, Claude, Open Source, LLM, Python, Pytorch, RAG Systems, and SQL.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Full Stack Engineer, AI, Anthropic, API, Artificial Intelligence, Backend, Docker, Frontend, Kubernetes, Next.js, Node.js, NoSQL, OpenAI, Claude, Open Source, LLM, Python, Pytorch, RAG Systems, SQL, Programming, Programmer Analyst, Software Engineer, Software Developer, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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