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Machine Learning Engineer Jobs in Somerville, MA

Machine Learning Engineer

Cambridge, MA ยท On-site

$135K - $200K/yr

... engineer with strong software fundamentals and a keen interest in collaborative problem-solving. Key Responsibilities: * ML Optimization and Deployment: Develop and deploy machine learning models for ...

Machine Learning Engineer - Edge

Lowell, MA ยท On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and candidates must reside within a commutable distance of one of our offices in either Dover, NH, or Lowell ...

Senior Machine Learning Engineer

Cambridge, MA ยท On-site

$133.90K - $176.50K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Design, provision, and maintain the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations. Write high-quality code that ...

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

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Showing results 1-20

Machine Learning Engineer information

See Somerville, MA salary details

$34.4K

$140.5K

$211.2K

How much do machine learning engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning engineer in Somerville, MA is $140,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $169,100.00 per year, depending on experience, location, and employer.

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 are Machine Learning Engineers?

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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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 are the most commonly searched types of Machine Learning Engineer jobs in Somerville, MA? The most popular types of Machine Learning Engineer jobs in Somerville, MA are:
What are popular job titles related to Machine Learning Engineer jobs in Somerville, MA? For Machine Learning Engineer jobs in Somerville, MA, the most frequently searched job titles are:
What cities near Somerville, MA are hiring for Machine Learning Engineer jobs? Cities near Somerville, MA with the most Machine Learning Engineer job openings:

Machine Learning Engineer

Ikigai Labs

Cambridge, MA โ€ข On-site

$135K - $200K/yr

Full-time

Posted 7 days ago


Job description

Company Descriptionย 

The Ikigai platform unlocks the power of generative AI for tabular data. We enable business users to connect disparate data, leverage no-code AI/ML, and build enterprise-wide AI apps in just a few clicks. Ikigai is built on top of its three proprietary foundation blocks developed from years of MIT research - aiMatch, for data reconciliation, aiCast, for prediction, and aiPlan, for scenario planning and optimization. Our platform enables eXpert-in-The-Loop (XiTL) for model reinforcement learning and refinement, at scale.

With a combination of enterprise expertise and deep research in the field of AI, Ikigai Labs helps scale enterprises with AI by solving data engineering and modeling problems for business users and data scientists alike. Our unique ability to unlock value in tabular and time series data through AI-powered data harmonization, forecasting, dynamic learning and planning, is our Ikigai, our purpose in the world of AI.

As an AI/ML Engineer at Ikigai Labs, you will be part of a high-performing team responsible for optimizing and deploying ML solutions to maximize performance and scalability. We seek a dynamic and passionate engineer with strong software fundamentals and a keen interest in collaborative problem-solving.

Key Responsibilities:

  • ML Optimization and Deployment:ย Develop and deploy machine learning models for optimal performance and scalability.
  • Productivity Tools Development:ย Build tools and services to enhance the ML platform, utilizing technologies like Kubernetes, Helm, and EKS.
  • Model Architecture:ย Apply a strong understanding of deep learning architectures (CNNs, RNNs, etc.) to solve complex problems.
  • Research Adaptation:ย Stay abreast of recent ML and deep learning literature and adapt findings to real-world applications.
  • Collaborative Development:ย Work with cross-functional teams to integrate AI and ML solutions that drive business value.
  • Data Handling:ย Manage large datasets and build ML pipelines for data processing and training.
  • ETL/ELT Processes:ย Design and develop scalable data integration processes.
  • Predictive Modeling Platform:ย Develop an on-demand predictive modeling platform using gRPC.
  • Cloud and Containerization:ย Utilize Kubernetes for managing Docker containers and various cloud services (AWS, Azure) to solve cloud-native challenges.
  • Stakeholder Management:ย Provide occasional support to our customer success team.

Technologies We Use:

  • Languages:ย Python3, C++, Rust, SQL
  • Frameworks:ย PyTorch, TensorFlow, Docker
  • Databases:ย Postgres, Elasticsearch, DynamoDB, RDS
  • Cloud:ย Kubernetes, Helm, EKS, Terraform, AWS
  • Data Engineering:ย Apache Arrow, Dremio, Ray
  • Miscellaneous:ย Git, Jupyterhub, Apache Superset, Plotly Dash

Qualifications:

  • Bachelorโ€™s degree in Computer Science, Math, Engineering, or related field (Master's preferred) with 0-5+ years of experience (depending on the level)
  • Strong understanding of data structures, data modeling, algorithms, and software architecture.
  • Proficient in probability, statistics, and algorithm development.
  • Hands-on experience with ML and deep learning libraries (Scikit Learn, Keras, TensorFlow, PyTorch, Theano, DyLib).
  • (Bonus) Experience with big data and distributed computing (Hadoop, MapReduce, Spark, Storm).
  • Proficiency in Python, AWS services, and ETL/ELT pipelines.
  • Understanding of key software design principles, design patterns, and testing best practices.
  • Experience with Kubernetes and/or EKS is a plus.
  • Ability to learn quickly in a fast-paced, agile environment.
  • Excellent organizational, time management, and communication skills.
  • Willingness to engage in pair programming, share knowledge, and provide and receive constructive feedback.
  • Strong problem-solving skills and the ability to take initiative.
Location Requirement: Candidates must reside in or near Cambridge, MA or San Mateo, CA. This role is not open to other locations at this time.

Equal Opportunity Employment:

Ikigai Labs is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants. We value diversity and are dedicated to fostering an inclusive environment for all employees, regardless of race, color, sex, gender identity or expression, age, religion, national origin, ancestry, citizenship, disability, military or veteran status, genetic information, sexual orientation, marital status, or any other characteristic protected under applicable law.

If you are passionate about machine learning and eager to make an impact, we would love to hear from you. Apply today to join the Ikigai Labs team and help us build the future of AI.

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