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Entrylevel Machine Learning Engineer Jobs in Cambridge, MA

MACHINE LEARNING ENGINEER , Jameel Clinic for Machine Learning, will lead deploying machine learning models developed in our labs; collaborate with researchers to improve novel algorithms; customize ...

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Entrylevel Machine Learning Engineer information

See Cambridge, MA salary details

$34.4K

$140.7K

$211.5K

How much do entrylevel machine learning engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for entrylevel machine learning engineer in Cambridge, MA is $140,741.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,900.00 and $169,400.00 per year, depending on experience, location, and employer.

Can I get into AI with no experience?

Entry-level machine learning engineer roles typically require some background in programming, mathematics, and data analysis, but many employers are open to candidates with foundational skills and a willingness to learn. Gaining experience through online courses, projects, and certifications in tools like Python and machine learning frameworks can help you qualify for such positions. Building a portfolio and understanding core concepts can improve your chances of entering the AI field without prior professional experience.

What engineers make $500,000?

Highly experienced senior engineers in fields such as software engineering, data engineering, and machine learning engineering can earn $500,000 or more annually, especially with bonuses, stock options, or in high-cost-of-living areas. Achieving this level typically requires advanced skills, extensive experience, and often leadership roles or specialized expertise in high-demand technologies.

What is the difference between Entrylevel Machine Learning Engineer vs Data Scientist?

AspectEntrylevel Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Math, or related; some knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, implements algorithms, collaborates with engineering teamsAnalyzes data, builds statistical models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles involve working with data and algorithms, an Entrylevel Machine Learning Engineer primarily focuses on developing and deploying machine learning models within software systems. In contrast, a Data Scientist emphasizes analyzing data, creating statistical models, and deriving insights. Both roles often require similar educational backgrounds, but their day-to-day tasks and industry applications differ.

Can I learn ML in 3 months?

As an entry-level machine learning engineer, gaining foundational knowledge in ML within three months is possible with intensive study, focusing on programming (Python), algorithms, and tools like scikit-learn or TensorFlow. However, developing deep expertise and practical experience typically requires longer, ongoing learning and project work.

Which 5 jobs will survive AI?

For entry-level machine learning engineers, roles that require complex problem-solving, creativity, and human judgment—such as data science, AI ethics, research scientist, AI product management, and specialized software development—are likely to persist despite AI advancements. These positions often involve designing, overseeing, and interpreting AI systems, which require deep domain knowledge and critical thinking that AI tools currently cannot fully replicate.
What cities near Cambridge, MA are hiring for Entrylevel Machine Learning Engineer jobs? Cities near Cambridge, MA with the most Entrylevel Machine Learning Engineer job openings:

Machine Learning Engineer II / Senior Machine Learning Engineer I, Physical Sciences

Lila Sciences

Cambridge, MA • On-site

$128K - $198K/yr

Full-time

Medical, Dental, Vision, Life

Posted 8 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 end-to-end 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).
  • Hands-on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
  • Clear communication and collaboration in cross-functional 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 open-source ML or scientific software.
  • Experience with workflow orchestration, data provenance, or large-scale compute environments.

Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$128,000-$198,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We're All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.