What are the responsibilities and job description for the Machine Learning Operations Engineer position at Cyvl?
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 We are in a phase of rapid growth, disrupting a massive and outdated market with our innovative solutions.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.
\n- 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.
- 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.
- 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.
- 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
- 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.
Salary : $130,000 - $175,000
