Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell® Fusion, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior. Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day.

CMT is looking for a creative, collaborative, and highly motivated Machine Learning Intern to help develop applied machine learning capabilities using real-world mobility and behavioral data. This internship is ideal for someone who enjoys solving ambiguous problems, building practical ML workflows, working with messy real-world datasets, and translating technical findings into clear recommendations.

The intern will work on a 12-week applied ML project involving data exploration, labeling strategy, feature engineering, model development, evaluation, and stakeholder-facing analysis. The ideal candidate has strong Python skills, a solid foundation in machine learning, strong initiative, and the ability to make progress in open-ended problem spaces.

Responsibilities:

• Explore real-world mobility datasets and identify useful behavioral, temporal, contextual, and aggregate patterns
• Help define practical data labeling guidelines, quality criteria, and edge-case handling rules
• Build and validate datasets for supervised machine learning experiments
• Develop baseline and improved ML models using Python and standard data science workflows
• Perform feature engineering, model evaluation, error analysis, and iteration
• Assess model performance across relevant data segments and edge cases
• Summarize findings, limitations, risks, and opportunities for technical and product stakeholders
• Produce clear documentation, analysis reports, and final recommendations

Qualifications:

• Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Data Science, Machine Learning, Statistics, Engineering, Applied Math, or a related quantitative field
• Strong Python programming skills and comfort working with real-world datasets
• Solid understanding of supervised machine learning, feature engineering, classification metrics, train/test splits, and error analysis
• Experience with common Python data science libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or similar tools
• Strong analytical and problem-solving skills, with a bias toward initiative and ownership
• Clear written and verbal communication skills, including the ability to explain technical findings to non-technical stakeholders

Compensation and Benefits:

• Fair and competitive hourly rate based on education level
• Flexible scheduling options depending on role and responsibilities

Additional Perks:

• Feel great working to improve road safety around the world!
• Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness
• CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all!

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

Your Impact at LILA

Join us in shaping the future of science! We are seeking Sr Principal, and Principal Software Engineers with full stack experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

Join us in shaping the future of science! We are seeking Staff, Senior II, and Senior I Software Engineers with either frontend or backend experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5-10 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

Your Impact at LILA

Join us in shaping the future of science! We are seeking a software engineer with a background in life sciences to join our data science team, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. This role spans web services and data engineering, with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

What You'll Be Building

• Participate in the entire software development life cycle, focusing on designing, implementing, and maintaining software services.
• Develop reusable code and libraries to improve efficiency and scalability.
• Align development with strategic goals, ensuring software supports broader organizational needs.
• Manage git repositories, team Jira board and Notion Hub, promote best practices, assist lab scientists with use of new tools, and foster a collaborative development culture.
• Work directly with scientists to identify gaps and unmet needs, develop tailored software solutions for data management, LIMS functionality, and data automation
• Support infrastructure as code and design efficient deployment strategies.
• Write clear, concise documentation for both engineers and end users.

What You’ll Need to Succeed

• Minimum of 2 years of experience writing software in a commercial setting.
• High-level proficiency in Python.
• Strong understanding of git best practices.
• Acute listening skills and patience to deeply understand user challenges.
• Experience implementing scalable software solutions.
• Excellent problem-solving skills and team-first mentality.
• Strong communication skills to effectively collaborate with team members and stakeholders.
• Energetic self-starter and independent thinker, with strong attention to detail.
• Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.

Bonus Points For

• Background in biological sciences
• Familiarity with data science and ML libraries (pandas, numpy, scipy).
• Knowledge of modern developer tools (pydantic, pyright, uv).
• Understanding of Kubernetes, ArgoCD, and GitHub Actions.
• Familiarity with AWS fundamentals (e.g., RDS, EC2, S3, EKS).

Your Impact at LILA

What You'll Be Building

• Developing, wrapping, and adapting domain-specific tools for molecular modeling, data analysis, process optimization, molecular modeling, and more
• Deploying custom, agentic scientific workflows that integrate with industrial instruments (PLCs, control software) and data systems (ERP, MES, SCADA)
• Building real-time data pipelines that transform messy scientific data into actionable insights
• Creating intuitive interfaces that make complex AI/ML capabilities accessible to scientists
• Architecting solutions that scale from proof-of-concept to enterprise-wide deployment

What You'll Need to Succeed

• Background in biology, molecular science, or related scientific field
• Outstanding communication skills—you'll interface directly with both executives and the manufacturing line
• Experience with data engineering, ETL pipelines, and working with complex/messy datasets
• Strong full-stack development skills with the ability to work across backend, frontend, and data layers
• Exceptional problem-solving abilities and comfort with ambiguous requirements
• Knack for product discovery and ability to pass requirements back to the platform
• Willingness to travel to customer sites for frequent and extended deployments

Bonus Points For

• Previous customer-facing or consulting experience
• Depth in controls engineering and machine learning
• Experience with scientific computing libraries (NumPy, Pandas, SciPy, RDKit)
• Familiarity with ML/AI implementation and deployment
• Familiarity with modern web technologies (TypeScript, React)

What Makes a Great FDE

• Customer Obsessed: You're energized by understanding customer problems deeply and seeing your solutions drive real impact
• Fast Learner: You quickly grasp new scientific domains and translate complex requirements into elegant solutions
• Autonomous: You thrive with minimal supervision and take extreme ownership of customer success
• Collaborative: You work seamlessly with both technical and non-technical stakeholders
• Technically Versatile: You're comfortable jumping between technologies and picking up new tools as needed

Ready to Transform Scientific Discovery?

If you're excited about embedding with world-class scientists, shipping impactful solutions at startup speed, and building the future of scientific software, we want to hear from you. Join us in our mission to accelerate breakthrough discoveries that will define the next century of human progress.

We are embarking on a transformative journey with DriveWell Atlas, a groundbreaking initiative to build a family of novel AIs on telematics data. As a Principal Machine Learning Engineer on the DriveWell Atlas team, you will be at the forefront of developing these next-generation AIs. You will lead innovative projects focused on designing, pre-training, fine-tuning, and deploying these AIs. Your work will directly contribute to enhancing our capabilities in risk assessment, driver engagement, and crash and claims processing. This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You will have an opportunity to build a first-of-its-kind LLM from petabyte-scale data. 

CMT is looking for a Principal Machine Learning Engineer, Foundation Models to help us change the world. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Use independent judgment and discretion to lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics 
• Develop and implement novel algorithms for modeling both automotive physics and human driving behavior 
• Pioneer advanced self-supervised learning techniques, including the design and implementation of innovative tasks tailored to multi-modal telematics sensor data to learn rich representations of movement and driver behavior 
• Develop models robust to noise, missing data, and diverse operating conditions typical of real-world mobile sensor and IoT datasets 
• Build and manage scalable training and inference pipelines using tools like Ray, PyTorch DDP, Horovod, or similar frameworks 
• Integrate these AIs into production systems while ensuring high performance and reliability
• Optimize these AIs for efficient deployment on various platforms, including cloud and edge/mobile devices 
• Collaborate closely with engineering, product, and research teams to translate cutting-edge research into impactful products and features for the DriveWell Atlas platform 
• Mentor junior scientists and contribute to the broader AI/ML strategy at CMT 
• Stay abreast of the latest AI advancements, evaluating and adopting emerging technologies and methodologies relevant to telematics 
• Contribute to efforts in AI explainability and interpretability 
• Complete any tasks as they arise

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field 
• 7+ years of professional experience in AI/ML 
• 3+ years of hands-on experience developing and deploying foundation models, with a strong portfolio in generative AI for sequential or spatio-temporal data 
• Strong, hands-on experience in building and training time-series transformer architectures for complex sensor fusion and behavioral modeling tasks is required 
• Deep expertise in designing pretraining tasks for self-supervised learning on noisy, real-world sensor data 
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn)
• Extensive experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow for large-scale model training and deployment 
• Solid understanding and practical experience with distributed training techniques and efficient training methodologies for large models 
• Experience building and maintaining large-scale data processing pipelines and machine learning infrastructure using tools like Spark, Airflow, Docker, and cloud platforms (e.g., AWS, GCP, Azure)
• Excellent problem-solving skills and the ability to translate complex business problems into tractable AI-based solutions 
• Strong verbal/written communication and collaboration skills, with the ability to effectively convey complex technical concepts to diverse audiences 
• Product-focused thinking with a proven ability to deliver impactful AI solutions

Nice to Haves: 

• PhD or Master's degree preferred 
• Experience with MLOps practices and tools for managing the lifecycle of machine learning models
• Publications in top-tier AI/ML conferences or journals 
• Familiarity with techniques for model interpretability and explainability (XAI) 
• Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and 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 and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $177,000 to $221,300. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

As a Principal Machine Learning Engineer at CMT, you will develop algorithms that represent physical phenomena associated with both vehicle and human movements when measured by cell phone sensors and IoT devices. You will solve challenging real-world problems and assist in the development of innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Using knowledge of statistics, machine learning / deep learning, signal processing, physics, programming and data modeling, the Principal Machine Learning Engineer consults on Data Science projects, and works independently on developing new solutions to achieve CMT’s objectives, and making valuable discoveries which lead to company-wide prototype development and product improvements. 

CMT is looking for a Principal Machine Learning Engineer to help us change the world. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Use independent judgment and discretion to spearhead the creation of innovative and cutting-edge algorithmic solutions, utilizing unconventional approaches to address complex challenges. These solutions should have a far-reaching impact on the company, and involve the development of new features and products for customers using diverse data sources 
• Lead and mentor a team of talented junior machine learning engineers, guiding them through every phase of solution development, from meticulous data pre-processing and advanced modeling, to rigorous testing, seamless roll-out, and continuous performance monitoring in live production environments
• Demonstrate exceptional communication skills to effectively convey and present complex data science concepts to stakeholders across the organization. Foster a collaborative environment by actively engaging with diverse teams and promoting cross-functional cooperation 
• Stay at the forefront of research and emerging trends in the field of data science. Evaluate and validate the potential impact of incorporating new ideas into the platform, products, and customer experiences, ensuring continuous enhancement and innovation 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Electrical Engineering, Physics or Mathematics 
• 7+ years of experience in the Data Science field 
• 3+ years of experience developing commercial software with strong algorithmic, AI/machine learning, or signal processing components 
• Deep understanding of data science principles, algorithms and practices, such as deep learning / machine learning, statistics and probability, signal processing, and sensor physics
• Must possess a thorough knowledge and practice of software development process in large scale, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn, SQL
• Advanced knowledge of Big Data infrastructure, computation and storage as well as scalable AI/ML platforms & tools, e.g. Spark, Ray, TensorFlow, Keras, Torch, Caffe, etc. 
• Strong visualization and data literacy skills, with demonstrated ability to summarize mathematical representations into simple data visualizations and statistical results 
• Strong customer-focus and presentation skills with the ability to obtain requirements and influence outcomes

Nice to Haves: 

• Master’s or Ph.D. preferred

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and 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 and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $177,000 to $221,300.  This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

CMT is building DriveWell Atlas, a family of foundation models trained on large-scale, multi-modal telematics signals (e.g., inertial sensors, GPS-derived signals, device/context features) to power safer driving outcomes across risk, safety, crash and claims workflows. 

As an IC2 Foundation Models contributor, you will work closely with senior scientists and engineers to prototype, train, evaluate, and deploy time-series foundation models—while also helping optimize the underlying training/inference systems for scale and efficiency. This role is hands-on, highly technical, and well-suited for someone with strong software fundamentals and growing applied ML experience. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Use independent judgment and discretion to develop ML / DL models which pattern driving behaviors and vehicle kinematics in data collected via smartphone sensors 
• Assist with projects and solutions through the full development stages, from data pre-processing, modeling, testing, through roll-out with minimum management oversight 
• Write code for debugging complex issues and creating new solutions that will run as part of production systems 
• Support customers’ requests regarding the production ML models and derive deep insights from data
• Use independent judgment and discretion to communicate and present data science work within the data science team as well as to stakeholders across the org and to collaborate across different teams 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Statistics, Mathematics or Engineering 
• 2+ years of professional experience in the Data Science field 
• A good understanding of data science principles, algorithms and practices, such as machine learning, deep learning, statistics and probability 
• Knowledge of software development process, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn and SQL 
• Ability to write and navigate code, request data from data sources and code from scratch
• Experience with deep learning frameworks (TensorFlow, Keras, Torch, Caffe, etc.) and knowledge of Big Data infrastructure (Hadoop, Spark, etc.) will be a plus 
• A great team player and quick learner

Nice to haves:

• Experience with one or more of the following:
• • Time-series / sensor modeling (inertial signals, GPS-derived features, mobile/IoT data)
  • Distributed systems or big-data processing (streaming/batch pipelines; e.g., Kafka/Spark/Ray-style ecosystems)
  • GPU programming / performance optimization (CUDA, kernel-level efficiency, profiling/benchmarking, mixed precision training, and memory/performance tuning)
  • Model compression techniques (post-training quantization, pruning)
  • Demonstrated ability to translate ideas into working prototypes (course projects, research, prior roles).

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and 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 and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $123,000 to $153,700. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

Parabilis Inc. is seeking a highly talented and motivated Senior Data Scientist / Cheminformatician to support the platform discovery engine for Helicon^TM peptide drugs. Reporting to the Associate Director of Cheminformatics, the candidate will work collaboratively with biologists and chemists, leveraging skills in data science and cheminformatics to enable hypothesis generation and data insights for advancing Fog preclinical drug discovery.

You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team ranging from computational biology, bioinformatics, computational drug discovery, research informatics and data engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science from building the discovery pipeline to supporting and developing our discovery platform.

Responsibilities

• Provide scientific leadership and data science / (chem)informatics expertise towards, but not limited to, hit identification, targeted screening of Helical peptide library designs, hit prioritization, hit-to-lead progression using multi-objective optimization, new drug-target assessments, and advancing drug-pipeline projects towards the clinic
• Analyze peptide/chemical structure and property space to identify patterns / gaps that inform Helicon and monomer designs
• Adapt and implement data analytics and machine learning techniques towards predictive models of Helicon^TM properties
• Contribute to implementation and development of cheminformatics and research informatics systems and tools for Fog
• Work with IT and data engineering to enable enterprise-level cheminformatics solutions

Requirements

• MS or PhD in Data Science, Cheminformatics, Computational Chemistry or Computational Biology, Chemistry, Biophysics, Macromolecular sciences, Computer Science, or related scientific field with 5+ years of experience within the pharmaceutical or biotechnology field
• Proven track record of impact in a drug discovery program using informatics/computational techniques
• Demonstrated expertise with cheminformatics (e.g. RDKit, ICM, OEChem) and data science toolkits/libraries (e.g. Pandas, Scikit-Learn, and Numpy)
• Demonstrated understanding of critical assessment of molecule-property data and predictive model quality
• Demonstrated expertise in data analytics and solid grasp of statistical principles
• Experience with data visualization techniques and exploration tools (e.g Vortex, Spotfire, Datawarrior, DataGrok)
• Strong scientific programming skills (Python). Familiarity with modern pipeline tools is a plus.
• Excellent communication and collaboration skills that contribute to and inspire a vibrant community of drug hunters
• Experience with (chem)informatics analyses of peptides, machine learning, databases/enterprise informatics systems (e.g. Dotmatics), or cloud computing environments (e.g. Google, AWS, Azure) is a plus

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $145,000 -$ 175,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being. 

As an equal opportunity employer, Parabilis Medicines values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity
• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases
• Design, implement, and scale robust computational pipelines for multi-omics analysis
• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results
• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable
• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.
• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis
• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)
• Experience with cloud computing platforms for large-scale data processing and with workflow management systems
• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments
• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations
• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000