Cambridge, MA

Data Jobs in Cambridge, MA

4 jobs found

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Today

Principal Machine Learning Engineer

Cambridge Mobile Telematics Cambridge, MA

Cambridge, MA

Today

$177k - $221k/yr Full time Backend Developer Python Artificial Intelligence

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Job Description

Build production machine learning systems that power risk assessment, engagement, and event detection across cloud and edge.

Design, build, and operate production ML systems at scale
Convert advanced models for sequential and multi-modal data into reliable products
Enable risk assessment, engagement, and event detection through ML-driven capabilities
Partner with research, product, and platform teams to deliver measurable business impact
Collaborate to deploy solutions across cloud and edge environments

Requirements

Master's degree or equivalent years of experience and/or certification in Data Science, Computer Science, Electrical Engineering, Physics, or Mathematics
7+ years of professional experience in AI/ML
3+ years hands-on experience developing and deploying deep learning models
Strong portfolio in generative AI for sequential or spatio-temporal data
Strong software engineering skills in Python
2+ years AWS experience with demonstrated knowledge of common AWS services, including EC2, S3, Lambda, Athena, Redshift, etc.
2+ years experience using computer languages such as Python, C++, Scala, etc.
Strong knowledge of SQL, including ability to comprehend and write complex SQL statements
Excellent problem solving, communication, and cross-functional collaboration

Technologies

Python
C++
Scala
AWS
EC2
S3
Lambda
Athena
Redshift
SQL

Nice to Haves

Ph.D. in a relevant field
Hands-on experience with time-series or multi-modal architectures for sensor fusion and behavioral modeling
Background in self-supervised learning on real-world sensor data and physics-informed modeling
Experience building large-scale data processing and orchestration, including Spark or Beam, Airflow, Kafka or Pub/Sub, Docker, and Kubernetes on AWS, GCP, or Azure
Publications in strong AI or ML venues

Compensation & Benefits

Annual performance bonus
Equity may be awarded in the form of Restricted Stock Units (RSUs)
Medical, Dental, Vision and Life Insurance
Matching 401k
Short-term & long-term disability
Parental leave
Unlimited Paid Time Off including vacation, sick days & public holidays
Flexible scheduling
Work from home policy depending on role and responsibilities
Fair and competitive salary based on skills and experience, with a base range of $177,000 to $221,300 for Cambridge, MA

Additional Perks

Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
Industry leader: 65 million drivers protected, powering 140+ programs across 25 countries
Recognized innovator in mobility AI, including TIME Industry Leader in AI, a Gold Edison Award, and the Artificial Intelligence Excellence Award for AI for Social Good
Great Place to Work Certified
High ownership, small teams, and direct access to leadership
Summer Fridays with half days to recharge
Join employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
Comprehensive wellness, education, and employee assistance programs

Diversity & Inclusion

Equal-opportunity employer committed to a workplace and culture where everyone feels valued, respected, and empowered
No discrimination based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability state

About Cambridge Mobile Telematics

World's largest telematics and AI company for safer mobility
Mission: make the world's roads and drivers safer
AI-driven platform DriveWell Fusion® helps proactively identify and reduce driving risk
Technology has helped prevent over 126,000 crashes worldwide
Helps partners measure risk, detect crashes, provide life-saving assistance, and streamline claims
Headquartered in Cambridge, MA with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia

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19d ago

AI Engineer, Enablement

LangChain Cambridge, MA

Cambridge, MA

19d ago

$150k - $195k/yr Full time AI Enablement Artificial Intelligence Engineer

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Job Description

LangChain is looking for an AI Engineer, Enablement to help customers build reliable agents using the LangChain ecosystem. This onsite role in Cambridge, MA blends technical depth with customer impact, from live workshops to scalable training assets. You will also support Enablement efficiency by building internal agents and tools.

Compensation for this position is $150,000 - $195,000 per year plus equity.

What you’ll work on

Design and deliver live, hands-on workshops that develop real product fluency rather than surface-level familiarity
Create enablement assets such as tutorials, reference implementations, and best-practice guides that scale beyond individual sessions
Provide technical guidance and office hours as questions come up from customer teams
Build internal agents and tools to streamline Enablement operations and automate processes so the team can scale efficiently
Act as the voice of the customer, feeding customer friction points back to Product and Engineering
Stay current on agent engineering practices and incorporate what you learn into the training you deliver

What you bring

3+ years building LLM/agent applications, including designing agent architectures and evaluation strategies
Strong Python with comfort writing and debugging code live in front of customers
2+ years in a technical, customer-facing role such as Enablement, Customer Success Engineering, Solutions Engineering, or similar, including experience delivering live workshops
Genuine enthusiasm for teaching, with a focus on leaving customers more capable than when you met them
Proven experience building and delivering high-quality technical training programs, including live workshops, written tutorials, documentation, and video guides
Exceptional presentation and communication skills to explain complex concepts to diverse audiences, from individual developers to enterprise stakeholders
Ability to operate independently in ambiguous situations and manage multiple customer engagements at once
Curiosity for continuous learning to identify evolving trends in agent engineering and quickly apply learnings to customer enablement materials
Willingness to travel up to 20% of the time

Helpful experience (nice to have)

Deployed AI agents in production, especially with LangChain, LangGraph, Deep Agents, or similar frameworks
Hands-on experience with LLM evaluation, observability, or guardrails
Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
TypeScript/JavaScript experience in addition to Python

Tech you’ll use

Python
LLM/agent applications
LangChain, LangGraph
Deep Agents
LangSmith

Benefits and support

Medical, dental, and vision coverage
Flexible vacation
401(k) plan
Meals on in-office days in the US

LangChain’s Enablement team helps customers build real fluency in agent engineering and the LangSmith platform through live training, hands-on workshops, and technical content designed to scale beyond 1:1 time. In this role, you’ll set the technical foundation for how customers learn to build reliable agents with the LangChain ecosystem, teaching teams to work effectively with LangChain, LangGraph, Deep Agents, and LangSmith through instructor-led workshops, written content, and reference implementations.

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1mo ago

IT Data Engineer – BB4352

TechData Service Company, LLC Cambridge, MA

Cambridge, MA

1mo ago Closed

$70 - $95/hr Contract Big Data Bigdata CI/CD

This position is no longer accepting applications (closed Sep 5, 2026).

Job Description

TechData Service Company, LLC is looking for an IT Data Engineer for an onsite contract role in Cambridge, MA. This position supports Discovery R&D and data science initiatives by building Databricks-based, scalable data platforms and automated scientific pipelines. You will work close to research and data teams to help ensure data workflows are reproducible, governed, and ready for downstream analytics.

How you’ll make an impact

Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and cloud-native technologies.
Build and optimize ETL/ELT processes across structured, semi-structured, and unstructured datasets.
Create data ingestion frameworks for research, laboratory, clinical, and external scientific datasets.
Implement data quality, validation, monitoring, and governance practices.
Support data lakehouse architecture and participate in data platform modernization efforts.
Develop and maintain Databricks notebooks, workflows, Delta Live Tables, and Databricks Jobs.
Apply Medallion Architecture (Bronze, Silver, Gold) to manage the data lifecycle.
Manage Delta Lake environments, optimizing performance, scalability, and cost.
Integrate Databricks with cloud-native services and enterprise applications.
Deploy, configure, and support the Seqera Platform (formerly Nextflow Tower).
Develop and maintain Nextflow pipelines for bioinformatics, genomics, imaging, AI/ML, and scientific computing workloads.
Integrate Seqera workflows with AWS infrastructure and compute environments.
Support containerized workflows using Docker and Kubernetes.
Design and implement cloud-based data solutions on AWS, including S3 and data lifecycle policies.
Build Infrastructure-as-Code solutions using Terraform or CloudFormation.
Implement security controls and access management aligned with enterprise IT standards.
Partner with data scientists, researchers, bioinformaticians, and stakeholders to clarify data requirements and support workflow automation.
Troubleshoot pipeline failures, performance issues, and workflow bottlenecks; contribute to platform roadmaps and continuous improvement.
SOPs, and knowledge articles.

What you bring

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Bioinformatics, or a related technical field.
5+ years of experience in data engineering, cloud engineering, or analytics platform development.
3+ years hands-on experience with Databricks and Apache Spark.
2+ years experience with Seqera Platform (Nextflow Tower) and Nextflow workflows.
Experience supporting scientific research, life sciences, pharmaceutical, biotech, or healthcare environments preferred.
Strong familiarity with: Databricks Lakehouse Platform, PySpark and Spark SQL, Delta Lake and Delta Live Tables, Databricks Workflows, and Unity Catalog.
Experience with SQL and Python, plus bioinformatics workflow automation.
Hands-on work with Docker and container orchestration via Kubernetes, including high-performance computing environments.
AWS required: S3, IAM, EC2, VPC, Lambda.
Infrastructure-as-Code with Terraform or CloudFormation, plus cloud monitoring and logging tools.
Practical experience across data lake and lakehouse architectures, ETL/ELT frameworks, data modeling, data cataloging, and governance.
Experience with API integrations, data quality frameworks, and development practices using GitHub or GitLab.
Knowledge of CI/CD pipelines and tools such as Jenkins or GitHub Actions, along with Agile and DevOps methodologies.

Compensation and role details

Location: Cambridge, MA (onsite)
Job type: contract
Pay: USD 70 - 95 per hour
Experience: minimum 2 years

Benefits

Dental insurance
Health insurance

Application questions

Where are you currently located?
What hourly rate are you seeking on a W2?

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1mo ago

Bioinformatics Data Scientist

Spectrix Analytical Services, LLC Cambridge, MA

Cambridge, MA

1mo ago Closed

$60+/hr Contract Python Amazon Web Services Analytics

This position is no longer accepting applications (closed Aug 20, 2026).

Job Description

Contribute to drug discovery and translational research by enabling computational proteomics, multi-omics analytics, scalable data workflows, and AI driven scientific analyses.

Responsibilities

Examine large scale proteomics and multi-omics data to support biomarker discovery, pharmacodynamic analysis, pathway and causal inference, disease biology, and drug discovery programs.
Design scalable, reproducible, cloud‑ready analytical workflows, data pipelines, reports, dashboards, APIs, and data products for scientific users.
Utilize statistical modeling, machine learning, and AI/LLM powered approaches to enhance biological interpretation, knowledge extraction, workflow automation, and scientific decision support.
Merge proteomics data with orthogonal modalities such as transcriptomics, genomics, genetics, perturbation data, metadata, and translational annotations.
Partner with computational scientists, mass spectrometry specialists, discovery biologists, translational researchers, and data science teams to define analytical strategies and clearly communicate results.
Champion data QC, reproducible analysis, workflow development, software engineering standards, and responsible use of AI‑assisted scientific tools.

Requirements

Doctorate in bioinformatics, computational biology, data science, statistics, computer science, systems biology, biology, biochemistry, chemistry, engineering, or a related quantitative field.
Hands-on experience with high‑dimensional biological or biomedical data such as proteomics, LC‑MS, Olink, SomaScan, transcriptomics, single‑cell data, spatial omics, genomics, genetics, or other omics modalities.
Strong proficiency in R and/or Python for data analysis, statistical modeling, visualization, and reproducible scientific computing.
Solid understanding of experimental design, data QC, normalization, missing-value assessment and imputation, feature selection, and advanced statistical modeling for high‑dimensional data, including linear and mixed‑effects models, Bayesian methods, biological signal deconvolution, pathway interpretation, and communicating findings.
Experience with scalable computing and cloud environments, including AWS services and workflow‑based analysis systems for large scientific datasets.
Proficiency with machine learning, AI, and LLM powered analytics, including developing robust agentic or multi‑agent frameworks for scientific workflows.
Familiarity with drug discovery, translational research, biomarker discovery, perturbation biology, pharmacodynamic studies, disease biology, or related biomedical contexts.
Ability to work independently on complex analytical problems and convey results clearly to scientific stakeholders.

Technologies

R
Python
AWS
Nextflow
Snakemake
Airflow
Docker
AWS Batch
ECS
DIA-NN
Spectronaut
MaxQuant
FragPipe
Proteome Discoverer
Skyline
Shiny
Dash
Streamlit
FastAPI
Flask
Posit/RStudio
Posit Connect
Claude
Parquet
SQL
Git
Olink
SomaScan

Benefits

401(k)
401(k) matching
Dental insurance
Employee assistance program
Flexible schedule
Flexible spending account
Health insurance
Health savings account
Life insurance
Paid time off
Parental leave
Professional development assistance
Referral program
Retirement plan
Tution reimbursement
Vision insurance

Preferred Qualifications

Postdoctoral, industry, or equivalent applied research experience after PhD.
Direct experience with computational proteomics across platforms such as LC‑MS proteomics, phosphoproteomics, DIA/SWATH, DDA, TMT, label‑free quantification, PTM analysis, spectral library generation and prediction, and affinity‑based proteomics such as Olink or SomaScan.
Hands‑on experience with proteomics software, outputs, or data structures from tools like DIA‑NN, Spectronaut, MaxQuant, FragPipe, Proteome Discoverer, Skyline, or similar platforms.
Experience building reusable scientific workflows, analytical pipelines, applications, dashboards, APIs, reports, or self‑service data products for scientists.
Experience deploying analytical workflows or data products on AWS or comparable clouds using Nextflow, Snakemake, Airflow, Docker, AWS Batch, ECS, or equivalent systems.
Experience delivering R and Python software and data products with Posit/RStudio, Posit Connect, Shiny, Dash, Streamlit, FastAPI, Flask, or similar platforms.
Strong software engineering practices including Git, modular code, documentation, testing, and reproducible workflow development.
Hands‑on experience building LLM enabled applications or workflows using Claude or other large language models, including RAG systems, tool‑using agents, prompt engineering, evaluation frameworks, LLMOps, or scientific knowledge extraction.
Experience applying ML or foundation-model approaches to biological data, including representation learning, multimodal modeling, classification/regression, embedding‑based retrieval, generative AI, or related methods.
Experience with data modeling, SQL, Parquet, metadata management, data lake architectures, or large scale biological data warehouses.
Strong publication record, open source contributions, or demonstrated delivery of reusable computational tools, analytical platforms, scientific workflows, or production quality internal data products.

Strong Differentiators

Ability to bridge computational proteomics, biological interpretation, cloud engineering, bioinformatics methodology development, and AI/ML/LLM workflow implementation for life science applications.
Proven success building tools, analytical methods, or platforms adopted by experimental, translational, or computational scientists.
Contributions to peer reviewed publications in bioinformatics, computational biology, proteomics, machine learning, systems biology, or related fields.
Experience designing AI assisted, machine learning, or agentic workflows that are reproducible, traceable, scientifically reliable, and suitable for biological and biomedical research.
Strong understanding of connecting omics data, pathway biology, perturbation data, genetics, and drug discovery questions into reusable analytical systems.
Ability to develop and publish novel analytical methodologies when appropriate.
Track record applying AI and ML techniques to life science datasets, including biomarker discovery, target identification, predictive modeling, knowledge extraction, or multi‑omics integration.
Ability to help shape future scientific AI strategy beyond executing predefined analyses.

Experience

Bioinformatics: 1 year (Preferred)

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Data Jobs in Cambridge, MA

Principal Machine Learning Engineer

AI Engineer, Enablement

IT Data Engineer – BB4352

Bioinformatics Data Scientist

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