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Machine Learning Engineer Jobs in Lexington, MA (NOW HIRING)

Base pay range $130,000.00/yr - $215,000.00/yr Direct message the job poster from Alsym Energy Alsym Energy is seeking a Machine Learning Scientist or Engineer to design, build, and deploy agentic AI ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Machine Learning Engineer II

Cambridge, MA · On-site

$106K - $145K/yr

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization ...

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Showing results 41-60

Machine Learning Engineer information

See Lexington, MA salary details

$35.4K

$144.7K

$217.4K

How much do machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer in Lexington, MA is $144,677.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $174,100.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

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

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

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

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

Infographic showing various Machine Learning Engineer job openings in Lexington, MA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $144,677 per year, or $69.6 per hour.

Machine Learning Engineer (Malden)

Malden, MA • On-site

$130K - $215K/yr

Full-time

Re-posted 7 days ago


Key responsibilities

  • Design, implement, and formalize scalable agent architectures that incorporate structured prompting and advanced tool‑use.

  • Create LLM Agents to autonomously retrieve proprietary scientific data, perform statistical analysis, and produce clear reports.

  • Collaborate with domain experts to understand data structures, define analysis requirements, and ensure statistical rigor in agent outputs.


Job description

This range is provided by Alsym Energy. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$130,000.00/yr - $215,000.00/yr

Direct message the job poster from Alsym Energy

Alsym Energy is seeking a Machine Learning Scientist or Engineer to design, build, and deploy agentic AI systems that actively support scientific discovery. This role focuses on developing LLM-based agents that can autonomously retrieve proprietary experimental and simulation data, perform statistically rigorous analyses, and generate clear, traceable reports for internal scientific teams. This position sits within the Discovery, and Early Prototyping (DEP) organization and works closely with domain experts in materials science, chemistry, and energy systems. The goal is not to build a generic chatbot, but to create reliable, production-grade agents that integrate knowledge across internal data silos and materially improve how scientists reason about data. Success in this role is measured by the delivery of production-ready agentic systems actively used by scientists for data analysis and decision-making.

Core Responsibilities
  • Infrastructure Development: Design, implement, and formalize scalable agent architectures, incorporating structured prompting and advanced tool‑use (tool‑augmented reasoning).
  • Agent Development: Create LLM Agents specifically engineered to:
  • Autonomously retrieve proprietary scientific data from diverse internal systems and formats (e.g., experimental, simulation).
  • Perform relevant statistical analysis on retrieved data.
  • Produce clear, actionable reports for internal users.
  • Domain‑Expert Interaction: Collaborate with domain experts in materials science to understand data structure, define analysis requirements, and ensure statistical rigor in Agent outputs.
Required Qualifications
  • Education: Master’s or PhD in Computer Science, Machine Learning, AI, Engineering, or a related scientific field, or equivalent research/industry experience.
  • Programming: Strong programming skills in Python and knowledge of software development best practices.
  • Agentic Frameworks: Expertise in LLM frameworks (Ollama, HuggingFace Transformers) and Agent‑building toolkits (LangChain, LlamaIndex, or similar).
  • Agentic Reasoning: Proficiency in advanced LLM reasoning methods, including Chain‑of‑Thought, self‑reflection, and advanced tool‑augmented reasoning.
  • Data & Statistics: Proven ability to access, process, and perform rigorous statistical analysis on complex, proprietary scientific datasets.
  • Self‑starter and energetic.
Preferred Qualifications
  • Research experience in causal reasoning, probabilistic programming, or symbolic AI.
  • Familiarity with scientific discovery pipelines in chemistry, materials science, or energy research.
  • Experience with multimodal reasoning (combining text, image, and experimental data).
  • Practical experience in delivering and maintaining production‑ready ML/Agentic systems.
Industry Background

Alsym Energy, Inc is a leading innovator in the rapidly changing field of battery energy storage. It is essential for the world to succeed in the transition to sustainable energy and batteries are at the very core of the solution. In fact, the IEA predicts that 60% of CO₂ emission reductions in 2030 will be directly related to batteries. This mission is what drives us every day. Over the last few years, supply‑chain constraints and significant safety incidents arising from lithium‑ion batteries have reduced confidence in the suitability of the technology. Alsym’s advanced sodium ion technology enables the highest performing non‑lithium‑ion battery in the industry, based on its safe, sustainable and long‑lasting energy storage solution.

Seniority level

Mid‑Senior level

Employment type

Full‑time

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