Senior Data & ML Engineer

Job Overview:

InVitro Capital is seeking a highly skilled Senior Data & ML Engineer to design and build the backbone of our data infrastructure—while also collaborating on high-impact machine learning projects. You’ll shape canonical data models, engineer robust pipelines, and help operationalize ML workflows that drive strategic decisions. We’re looking for an engineer who brings strong analytical thinking and is comfortable working with statistical and mathematical complexity as part of designing robust data and ML systems. If you’re excited by both infrastructure and modeling, and want to work with cutting-edge startups, this role is for you.

Working Hours: Monday to Friday, Pacific Time Zone. This is a hybrid position; team members are expected to work from our Irvine office at least once a week for in-person collaboration.

Key Responsibilities:

• Data Architecture & Modeling: Design and implement canonical data models (dimensional schemas, data vaults, feature stores) to support analytics and machine-learning pipelines.
• ETL & Pipeline Development: Build, schedule, and monitor batch and streaming data ingestion processes using Airflow (or equivalent), dbt/Dagster, Kafka, and Spark Structured Streaming.
• Cloud Data Platforms: Develop and optimize data workflows on Snowflake, BigQuery, or Redshift; manage relational databases (PostgreSQL/MySQL) and NoSQL stores (MongoDB, DynamoDB).
• Feature Engineering & ML Integration: Collaborate with data science to operationalize feature extraction, validation, and serving; ensure model inputs are performant and reproducible.
• Infrastructure & Deployment: Containerize services with Docker and Kubernetes; provision and manage resources via Terraform or CloudFormation; integrate CI/CD pipelines for data code.
• Quality & Governance: Implement data quality tests (Great Expectations or similar), monitoring, and lineage tracking; enforce documentation, version control, and best practices.
• Cross-Functional Collaboration: Work with analytics, engineering, and product teams to align data products with business goals and deliver reliable, timely insights.
  

Requirements

Minimum Requirements:

• 7+ years of experience in data engineering, ML engineering, or analytics engineering
• Strong Python and SQL skills; production experience with ETL orchestration tools (e.g., Airflow, Dagster)
• Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift) and streaming platforms (Kafka, Spark)
• Proven ability to design data models (star/snowflake schemas, data vault, graph models) and scale pipelines in production
• Comfort working with large, unstructured datasets and collaborating on model fine-tuning
• Solid understanding of data modeling principles, ETL best practices, and feature-store concepts
• Strong communication skills; able to bridge technical and non-technical stakeholders and translate requirements into data solutions
  

Preferred Requirements:

• Experience with dbt or Dagster for transformation and testing
• Familiarity with feature-store frameworks (Tecton, Feast) or custom implementations
• Prior work in machine-learning operations (MLflow, DVC, Weights & Biases)
• Background in finance, logistics, telecom, or retail analytics
• Exposure to messaging systems (RabbitMQ, AWS SNS/SQS) and event-driven architectures

Benefits

Why Join Invitro Capital?

• Work on cutting-edge AI and B2B technologies: We are at the forefront of AI and B2B innovation. Our employees have the opportunity to work on the latest and greatest technologies, and to make a real impact on the SME market.
• Help build and grow successful startups: We are committed to helping our portfolio companies succeed. Our employees play a vital role in building and growing these companies. This is not a 9 to 5 job. This is a startup environment with a give-it-all mentality.
• Work with some of the best minds in the industry: You will be part of a team of seasoned entrepreneurs and product leaders who are on a mission to make a difference in the SME space. You will have the chance to work with some of the best minds in the industry.
• Supportive and collaborative work environment: We believe in creating a supportive and collaborative work environment where our employees can thrive.
• Competitive compensation: We offer a competitive compensation package, with salaries ranging from [$2,200 to $3,000 monthly].