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Machine Learning Operations Engineer I
S&P Dow Jones Indices
Cambridge, USA
Full-time
Junior · 1+ years experience
Onsite
Discovered 1 weeks ago
Full Job Posting
What You’ll Do
- Iterate on Kensho’s ML processes to develop tools, services, and frameworks that make every stage of the ML workflow robust, auditable, and usable.
- Work closely with ML engineers to understand their unique processes, identify pain points, and form effective solutions.
- Empower engineers with the stable tooling necessary to rapidly experiment and actualize their research into demonstrable prototypes and mature products
- Evaluate, select and champion open source and third-party solutions, driving their adoption across teams and integrating into Kensho’s existing platform ecosystem
- Ship scalable, efficient, and automated processes for model fine-tuning and reinforcement learning and for the evaluation of LLMs/Agents
- Improve LLM and Agentic observability to help monitor agentic applications in production, detecting performance, decay and drift issues
- Stay at the frontier by actively tracking emerging tools and frameworks, promote best practices and strengthen the technical expertise of the team with your unique skill set
- What We Are Looking For:
- 1+ years of experience in ML infra, ML Ops, ML Engineering or some similar skillset
- Experience with Kubernetes
- Cloud Platform (AWS) understanding. We utilize tools like EKS and managed ML services like Bedrock and SageMaker
- Python proficiency (we are a Python shop mostly)
- Familiarity with distributed computing frameworks and workflow orchestration (ie. Ray, Airflow) is a big plus
- Familiarity with software engineering best practices in an ML context
- Some basic 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 and best practices across multiple teams
- Someone who’s very curious, driven, low-ego and eager to learn across a range of engineering disciplines, while being part of a fantastic team
- Technologies & Tools We Use:
- Development: Python, Bash, LangGraph, PyTorch
- Infrastructure: Ray, Amazon EKS, Airflow, Jsonnet, Terraform
- Ops: Git, AWS, LangFuse, Sentry, Prometheus, WB
- How To Really Get Our Attention:
- Experience with:
- Agentic AI systems, tools, frameworks and workflows
- MCP server patterns
- Eval pipelines
- At Kensho, we pride ourselves on providing top-of-market benefits, including:
- Medical, Dental, and Vision insurance
- 100% company paid premiums
- Unlimited Paid Time Off
- 26 weeks of 100% paid Parental Leave (paternity and maternity)
- 401(k) plan with 6% employer matching
- Generous company matching on donations to non-profit charities
- Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences
- Plentiful snacks, drinks, and regularly catered lunches
- Dog-friendly office (CAM office)
- Bike sharing program memberships
- Compassion leave and elder care leave
- Mentoring and additional learning opportunities
- Opportunity to expand professional network and participate in conferences and events
- Recruitment Fraud Alert:
- If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to [email protected]. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.
- We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with an additional office location in New York City. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
Qualifications
- Experience with Kubernetes
- Familiarity with distributed computing frameworks and workflow orchestration (ie. Ray, Airflow) is a big plus
- Familiarity with software engineering best practices in an ML context
About S&P Dow Jones Indices
Market Research & Analytics35000 employeesFounded 1860
Global provider of financial intelligence, ratings, and market analytics.
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