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Freelance Nvidia Machine Learning Jobs in Washington

What Impact You'll Have We are searching for a machine learning (ML) engineer in support of our ... NVIDIA Triton Inference Server), GPU memory management, and batching/quantization tradeoffs

Monitor AI machine learning biotechnology and national security policy trends Skills * A/B | A/B ... Flexible schedule | Freelance opportunities | Part-time hours | Project based work * Part-time ...

Autonomy SME, Lead

Washington, DC · On-site

$62.25 - $85.50/hr

Responsibilities : • Design and train machine learning models for perception, object detection ... hardware, such as NVIDIA Jetson, GPUs, and embedded platforms • Experience with robotics ...

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Freelance Nvidia Machine Learning information

What does a freelance Nvidia machine learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.

What are the key skills and qualifications needed to thrive as a freelance Nvidia machine learning specialist?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

What are some common challenges freelance Nvidia machine learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What is the difference between Freelance Nvidia Machine Learning vs Freelance Data Scientist?

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are the most commonly searched types of Nvidia Machine Learning jobs in Washington?

The most popular types of Nvidia Machine Learning jobs in Washington are:

What are popular job titles related to Freelance Nvidia Machine Learning jobs in Washington?

For Freelance Nvidia Machine Learning jobs in Washington, the most frequently searched job titles are:

What cities in Washington are hiring for Freelance Nvidia Machine Learning jobs?

Cities in Washington with the most Freelance Nvidia Machine Learning job openings:

Machine Learning Engineer, Detection and Tracking AI & Engineering Washington, DC

helsing.ai

Washington, DC • On-site

$180 - $240/hr

Other

Medical, PTO

Posted yesterday

New


Job description

Machine Learning Engineer, Detection and Tracking
  • Full-time
  • Washington, DC
Who we are

Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems.

The role

You will own the detection and tracking models that power Helsing's products — training, tuning, and deploying models against US-specific datasets. This is an applied ML role: you won't be writing research papers, but you will be expected to have strong intuition for model performance, data quality, and the practical trade-offs involved in getting detection and tracking systems to work reliably in production. You will manage the full model lifecycle — from assessing and curating training data through annotation, training, evaluation, and deployment to edge platforms.

The day-to-day
  • Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN, and similar architectures) on mission-specific datasets
  • Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack, or similar)
  • Evaluating model performance: analyzing metrics, diagnosing failure modes, and iterating on data and model improvements
  • Managing the data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets, and implementing augmentation strategies
  • Optimizing models for deployment on SWaP-constrained and embedded platforms (quantization, pruning, TensorRT, ONNX export)
  • Collaborating with systems engineers to integrate models into the broader Altra platform
  • Working across sensor modalities as needed, including electro-optical, infrared, and other imaging sources
You should apply if you
  • Have 5+ years of experience in applied machine learning or computer vision
  • Have a Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred
  • Have production experience training and deploying object detection models — not just research or academic projects
  • Are proficient in Python and PyTorch or a comparable deep learning framework
  • Have strong intuition for data quality; you can look at annotated datasets, training curves, and evaluation metrics and know what's wrong
  • Have experience with the full model training lifecycle: data curation, annotation management, training, evaluation, and deployment
  • Have experience optimizing models for deployment on SWaP-constrained and edge platforms (TensorRT, ONNX, quantization)
  • Understand multi-object tracking and have implemented or worked with tracking algorithms in practice
  • Can read and contextualize scientific papers in computer vision and apply findings to production systems
  • Are a U.S. citizen with an active security clearance or the ability to obtain one
Nice to have
  • Strong proficiency in Rust or C++ for production model deployment and optimization
  • Experience with multiple sensor modalities — particularly infrared or thermal imaging
  • Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registries
  • Experience with annotation tools and workflows (CVAT, Label Studio, or similar)
  • Background in computer vision beyond detection — segmentation, pose estimation, activity recognition
  • Experience with simulators, emulators, or synthetic data generation for training and evaluation
  • Experience deploying models on GPU-accelerated embedded platforms (NVIDIA Jetson, similar)
  • Background in defense, intelligence, or other mission-critical environments
Join Helsing and work with world-leading experts in their fields

Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns

The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world

Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward

In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts

We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practice responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about

What we offer

A focus on outcomes, not time-tracking

A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time.

Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.

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