MLOps Engineer: Build Scalable AI Platforms

Kensho; Cambridge (MA); On-site; USD 130,000 - 175,000; Full time

Benefits offered by this job

Medical, Dental, Vision insurance

401(k) with matching

Parental Leave

Job summary

Kensho is seeking an MLOps Engineer in Cambridge, MA to empower ML engineers with state-of-the-art tooling and infrastructure. You’ll iterate on ML workflows, collaborate with ML teams to identify pain points, and help productionize research into robust, scalable models and agents.

You’ll work across infrastructure and ML topics, improving observability and deploying automated processes for fine-tuning, RL, and evaluation of LLMs.

Qualifications

• 2+ years of experience in ML infra, ML Ops, ML Engineering or similar skillset.
• Experience managing distributed systems with Kubernetes; understand concepts and trade-offs.
• Cloud Platform (AWS) understanding; familiarity with EKS and managed ML services like Bedrock and SageMaker.
• Python proficiency; you’ll be working in a Python shop.
• Familiarity with distributed computing frameworks and workflow orchestration (Ray, Airflow).
• Familiarity with software engineering best practices in ML context; understanding of ML concepts, LLMs and agents.
• Ability to debug distributed systems across infrastructure, networking and application layers.
• Excellent communication skills to drive adoption of new tools across teams.
• Curious, driven, low-ego, eager to learn across engineering disciplines.

Responsibilities

• Iterate on Kensho’s ML processes to develop tools, services, and frameworks for robust ML workflows.
• Collaborate with ML engineers to understand processes, identify pain points, and implement solutions.
• Provide stable tooling to enable rapid experimentation and productionize research into prototypes and mature products.
• Offer resources and training for ML teams on best practices for productionizing work for high-value products.
• Evaluate and champion open source and third‑party solutions across teams and integrate into Kensho’s platform.
• Ship scalable, automated processes for model fine‑tuning, RL, and evaluation of LLMs/Agents.
• Improve LLM and Agentic observability to monitor production apps and detect issues.
• Stay at the frontier by tracking tools/frameworks and promoting best practices.

Skills

ML infra

Kubernetes

AWS

Python

Ray/Airflow

ML concepts

Debugging distributed systems

Communication

Curiosity

Tools

Ray

Airflow

Terraform

Git

SageMaker

Bedrock

Job description

Kensho is seeking an MLOps Engineer in Cambridge, MA to empower ML engineers with state-of-the-art tooling and infrastructure. You’ll iterate on ML workflows, collaborate with ML teams to identify pain points, and help productionize research into robust, scalable models and agents.

You’ll work across infrastructure and ML topics, improving observability and deploying automated processes for fine-tuning, RL, and evaluation of LLMs.