Lead the development of ML platforms, optimize data workflows, support model training and deployment, and collaborate across teams.
About Us:
Cyvl is a Boston-based tech startup revolutionizing the way civil engineering firms and governments map and manage transportation infrastructure. Our enterprise-grade hardware and software solutions leverage 3D mapping sensors to capture LiDAR, imagery, and GPS data, retrofitted to our customers' vehicles. This data is processed through our AI-powered cloud pipelines to generate actionable condition and geospatial reports, saving our customers time, money, and resources. We are in a phase of rapid growth, disrupting a massive and outdated market with our innovative solutions.
About the Role:
As an MLOps Engineer at Cyvl, you will lead the development of the platforms and tooling that empower our Machine Learning team to move quickly and efficiently. Your primary focus will be optimizing our data curation and annotation workflows, ensuring that all labeled datasets and metadata are centrally organized, easily discoverable, and reusable. Beyond data management, you’ll also support experimentation, model training, and deployment workflows to help us bring ML solutions to production faster and with greater reliability. This is a highly cross-functional role where you’ll collaborate with ML engineers, software engineers, and product managers to enable scalable and reproducible machine learning systems.
Responsibilities:
- Build and maintain scalable pipelines for data ingestion, preprocessing, labeling, and metadata management.
- Centralize all ML annotations, datasets, and labels using best-in-class data management and labeling tools.
- Evaluate and integrate third-party tools and frameworks to increase efficiency of the ML development process.
- Contribute to infrastructure decisions and promote best practices across the MLOps lifecycle.
- Design and maintain platforms that accelerate ML experimentation, hyperparameter tuning, and training workflows.
- Collaborate with ML engineers to streamline and automate deployment of models to production environments.
Required Skills:
- 3+ years of experience in an MLOps or related role, supporting a team of at least 3 ML engineers.
- Strong hands-on experience with Kubernetes and container orchestration for ML workloads.
- Experience with the AWS SageMaker suite of tools
- Familiarity with modern data labeling and management platforms (e.g., Label Studio, Kili, Scale AI, CVAT, Prodigy, Postgres, etc.).
- Experience designing, maintaining, and scaling ML pipelines and tooling.
- Proficiency in Python and experience with ML libraries (e.g., PyTorch, TensorFlow, scikit-learn).
- Experience with the Go programming language
- Experience with experiment tracking tools (e.g., MLflow, Weights & Biases).
- Strong knowledge of DevOps, CI/CD practices, and cloud infrastructure (AWS preferred).
- Excellent communication and collaboration skills, with the ability to work effectively across teams.
Nice to Have:
- Experience with data versioning tools like DVC or LakeFS.
- Exposure to data lake / warehouse solutions like Snowflake or BigQuery.
- Knowledge of vector databases and semantic search.
- Familiarity with Argo Workflows
- Previous work in startup or high-growth environments.
- Background in building internal tools and dashboards for ML teams.
Ideal Cyvl Candidate:
- Self-motivated, self-starter with a zeal to win
- Great communicator; strong oral and written skills
- Ability to think creatively
- Hands-on problem solver who enjoys cracking difficult nuts
- Quick study – able to pick up and apply new concepts in a hurry
- Track record of achievement
- Enjoys working on and helping to build outstanding teams
- Demonstrates an entrepreneurial spirit and gets stuff done
What We Offer:
- Competitive salary and equity package
- Comprehensive health, dental, and vision insurance
- Opportunities for professional growth and development
- A collaborative and innovative work culture with a tight-knit team of ~25 employees
If you're passionate about building powerful ML platforms, and you thrive on enabling teams to move faster and smarter with their data, we want to hear from you. At Cyvl, you’ll have the opportunity to take ownership of critical MLOps infrastructure, shape the way our ML engineers work, and have a direct impact on our product and customers. Join us in transforming the future of infrastructure with AI and world-class tooling.
Top Skills
Argo Workflows
Aws Sagemaker
BigQuery
Cvat
Dvc
Go
Kili
Kubernetes
Label Studio
Lakefs
Mlflow
Postgres
Prodigy
Python
PyTorch
Scale Ai
Scikit-Learn
Snowflake
TensorFlow
Weights & Biases
Cyvl Somerville, Massachusetts, USA Office
444 Somerville Ave, , Somerville, Massachusetts , United States, 02143
Similar Jobs
Consumer Web • eCommerce • Software
The Senior Machine Learning Operations Engineer enhances and maintains the ML platform, deploying models, building APIs, and collaborating with data scientists on scalable systems.
Top Skills:
AWSDockerGithub ActionsNumpyPandasPythonPyTorchSagemakerScikit-LearnSnowflakeSQLXgboost
Artificial Intelligence • Robotics • Automation
As a Machine Learning Operations Engineer, you will build and maintain ML pipelines, optimize model performance, and develop tools for model training and deployment.
Top Skills:
AWSEc2EksLinuxNumpyOpencvPythonPyTorchS3SagemakerTerraform
Artificial Intelligence • Robotics
As a Machine Learning Operations Engineer, you will design and maintain ML platforms, enhance observability, and collaborate with various engineering teams to enable machine learning applications.
Top Skills:
AWSCi/CdDatadogDockerFluentdGCPGitGrafanaKubernetesPrometheusPythonTerraform
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
