MLOps Engineer
Boston
$250,000 + Equity
Company Overview
A privately held, early-stage technology company is at the forefront of applying artificial intelligence to revolutionize the scientific method. Backed by a leading investment firm, this company is driven by the vision and resources needed to achieve groundbreaking results. Their life sciences initiative uses AI and high-throughput automation for discovering and developing valuable therapeutics across a range of biological fields.
The team thrives on cross-functional collaboration, actively reimagining how diverse teams work together. They embrace an inclusive mindset, encourage diversity of thought, and foster an environment where all voices are heard. Their approach values passion and recognizes that experience comes in many forms.
The Role
This company is looking for a skilled Machine Learning Operations Engineer (ML Ops) to join its growing team. The role focuses on building and maintaining cloud infrastructure to support large-scale machine learning model training. The successful candidate will work alongside a cross-functional team of experts, including biologists, software developers, and machine learning scientists, to push the boundaries of scientific discovery through AI-driven innovations.
Key Responsibilities:
- Manage and optimize a large cloud-based computing cluster supporting machine learning tasks.
- Implement and maintain MLOps practices to enhance the model development and deployment processes.
- Collaborate with interdisciplinary teams to integrate ML models into data pipelines.
- Ensure rigorous testing, performance benchmarking, and proper documentation throughout the development cycle.
Qualifications:
- Master’s degree (or equivalent experience) in computer science, computational biology, physics, or another quantitative field.
- Experience managing Kubernetes clusters on cloud-based GPU infrastructures.
- Familiarity with MLOps tools and practices, including version control, automated testing, and CI/CD processes.
- Expertise in machine learning computing with frameworks like PyTorch and Python data science libraries.
- Experience with managing large-scale multi-GPU training environments.
- Knowledge of additional high-performance libraries such as Accelerate or DeepSpeed is a plus.
About People in AI
At People in AI, we specialize in connecting top-tier machine learning, AI, and MLOps talent with pioneering companies like the one in this job description. As a leading AI recruitment agency in the US, we pride ourselves on our deep industry knowledge and commitment to finding the perfect match between candidates and businesses. Whether you're a company looking to build a cutting-edge AI team or a professional seeking the next exciting challenge in AI, People in AI is here to support your journey. Visit our website to learn more about how we can help transform your hiring process or assist you in advancing your career.
