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Machine Learning Engineer Biotech Jobs in Massachusetts

Machine Learning Engineer

Cambridge, MA ยท On-site

$125K - $150K/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

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 ...

Senior Machine Learning Engineer

Boston, MA

$113K - $155K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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 ...

Machine Learning Engineer - Edge

Lowell, MA ยท On-site

$86K - $135K/yr

Machine Learning Engineer - Edge Turn up the volume on your career as Cloud AI/ML Engineer GN brings people closer through our advanced intelligent hearing, audio, video, and gaming solutions.

Senior Machine Learning Engineer Work Locations (2) Submit Resume Imagine what you could do here! The people here at Apple don't just create products -- they build the kind of wonder that ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$161K - $246K/yr

ASUS Robotics & AI Center Senior Machine Learning Engineer The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role ...

Senior Machine Learning Engineer

Cambridge, MA ยท On-site

$133K - $176K/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 ...

In this role, you will collaborate closely with Machine Learning Engineers, BI Specialists, Sales and Marketing Leaders, and IT partners to execute AI and Advanced Analytics initiatives that will ...

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

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 ...

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.

Senior Machine Learning Engineer

Andover, MA

$105K - $145K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team ...

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Machine Learning Engineer Biotech information

What does a Machine Learning Engineer do in the biotech industry?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in Biotech, and why are they important?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are the most commonly searched types of Machine Learning Engineer Biotech jobs in Massachusetts? The most popular types of Machine Learning Engineer Biotech jobs in Massachusetts are:
What cities in Massachusetts are hiring for Machine Learning Engineer Biotech jobs? Cities in Massachusetts with the most Machine Learning Engineer Biotech job openings:
Infographic showing various Machine Learning Engineer Biotech job openings in Massachusetts as of May 2026, with employment types broken down into 19% Internship, and 81% Full Time. Highlights an 74% In-person, and 26% Remote job distribution.

Machine Learning Engineer

Ikigai Labs

Cambridge, MA โ€ข On-site

$125K - $150K/yr

Full-time

Posted 16 days ago


Job description

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

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

Qualifications:
  • Bachelor'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.