Staff Machine Learning Engineer
New
M
MotionalAutonomous Vehicles
We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.Full-TimeStaff
Salary205,000 - 272,500 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSPythonGCPMachine LearningPyTorchAzureTensorflowCI/CDSoftware EngineeringDeep LearningMLOps
Requirements
- BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience)
- 8+ years of hands-on ML engineering experience, with a proven track record of owning architecture, deployment, and optimization of large-scale ML systems
- Demonstrated experience working with multimodal foundation models in ML production systems
- Demonstrated technical leadership: defining multi-quarter roadmaps, leading multi-person initiatives, and driving department-level technical strategy
- Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX)
- Strong software engineering fundamentals (system design, CI/CD, containerization)
- Broad ML generalist knowledge, with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale
- Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency
- Proven ability to mentor peers, explain complex trade-offs to leadership, and drive consensus across disparate teams
Responsibilities
- Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems.
- Own the system-level architecture for complex ML products, designing scalable frameworks for massive data mining and highly optimized, real-time inference.
- Lead multi-person projects to completion across teams and influence partner teams' technical roadmaps.
- Establish department-wide standards for ML system design, code quality, testing, and deployment.
- Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems.
- Act as a role model and technical go-to person, coaching Senior and junior engineers and leading architectural reviews.
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