Machine Learning Engineer
Develop scalable ML services for data enrichment, managing the full lifecycle from model training with PyTorch/TensorFlow to deploying optimized inference using ONNX/vLLM. Requires 5+ years experience in production ML systems, strong deployment skills, and software engineering proficiency.
About the job
What you'll do
- Design and build scalable ML services for enrichment workflows, including model training pipelines and high-performance inference APIs
- Deploy and optimize models using modern inference libraries and frameworks (ONNX, vLLM, TensorRT, etc.) to achieve low-latency, high-throughput performance
- Collaborate with software engineers and product teams to define data requirements, feature engineering strategies, and model evaluation metrics
- Build robust monitoring, observability, and evaluation systems to ensure model quality and service reliability in production
- Stay current with emerging ML techniques, tools, and best practices, particularly in areas like model optimization, efficient inference, and large-scale data processing
What we look for
- 5+ years of experience building and deploying machine learning systems in production environments
- Strong proficiency with model deployment technologies (Kubernetes, Ray, etc.) and inference libraries (ONNX, vLLM, TensorRT, or similar). Proficiency with model training frameworks (PyTorch, TensorFlow, Jax)
- You've successfully designed and scaled ML services that process large volumes of data and serve predictions with strict latency and throughput requirements
- Experience with the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring
- Solid software engineering skills, including experience with distributed systems, APIs, and cloud infrastructure
- You have a passion for building reliable, performant ML systems and understand how they create value for end users
What we offer
Competitive Salary The salary range for this position is $150,000 - $215,000 + equity. Within the range, individual pay is determined by experience, relevant education, and/or training.
Comprehensive Benefits
- Health, dental, and vision insurance
- Remote friendly with WeWork access
- Unlimited PTO, shared downtime during the federal holiday calendar, and company-wide off time at the end of each year
- 401(k) match
- Lifestyle & wellbeing stipends
- Salary top-up during military reserve duty
- Fully paid parental leave
- Child and pet care reimbursement during travel
Skills
PyTorch, TensorFlow, JAX, Onnx, vLLM, TensorRT, Kubernetes, Ray, Hugging Face
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