ZipRecruiter

Log In

1

Internship Machine Learning Quant Jobs in Lexington, MA

previous page

Showing results 41-60

All JobsMachine Learning Quant JobsInternship Machine Learning Quant JobsInternship Machine Learning Quant Jobs in Lexington, MA

Internship Machine Learning Quant information

See Lexington, MA salary details

$28.6K

$47.8K

$98.9K

How much do internship machine learning quant jobs pay per year?

As of Aug 16, 2026, the average yearly pay for internship machine learning quant in Lexington, MA is $47,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,500.00 and $51,700.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

What job categories do people searching Internship Machine Learning Quant jobs in Lexington, MA look for?

The top searched job categories for Internship Machine Learning Quant jobs in Lexington, MA are:

What cities near Lexington, MA are hiring for Internship Machine Learning Quant jobs?

Cities near Lexington, MA with the most Internship Machine Learning Quant job openings:

Internship Machine Learning Quant jobs near you

Senior Machine Learning Engineer I, Physical Sciences

Lila Sciences

Cambridge, MA

$133K - $176K/yr

Full-time

Re-posted 13 days ago

Job description

Your Impact at LILA

This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity scientific use cases in materials, chemistry and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today's greatest challenges in physical sciences.

What You'll Be Building

  • Design, implement, and maintain endtoend ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
  • Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
  • Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
  • Contribute to technical design reviews, coding standards, and mentoring of best practices.

What You'll Need to Succeed

  • BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
  • Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
  • Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
  • Handson experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
  • Clear communication and collaboration in crossfunctional settings.

Bonus Points For

  • Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
  • GPU optimization experience (CUDA, Triton, compilation, distributed training).
  • Prior contributions to opensource ML or scientific software.
  • Experience with workflow orchestration, data provenance, or largescale compute environments.

Apply