Senior Machine Learning Engineer, Platform Data Science and AI

About the Company

Labviva is on a mission to accelerate the pace of life science research. We connect researchers with suppliers of reagents, chemicals and instrumentation in an intuitive user-friendly platform that supports the priorities of scientists while staying compliant with purchasing rules.

We are a venture-funded start-up that acknowledges that the unique contributions of each team member drive our success. We commit to creating a diverse and inclusive workspace where people can make a positive impact. At Labviva, we invest in our employees and strongly believe that a culture of respect and support drives success for all involved.

This role is based out of our corporate headquarters office in Boston. We are a flexible hybrid environment with 3 days a week (Tuesday, Wednesday, Thursday) in the office. Please note that we are only accepting candidates that reside in the greater Boston area.

About the Role

We are looking for a seasoned Machine Learning Engineer to join our Platform Data Science and Artificial Intelligence team. Reporting to the Engineering Manager, Platform Data Science and Artificial Intelligence, you will play a critical role for driving the productionization of machine learning, focusing on the repeatable delivery, release, and deployment of diverse ML/AI models. You will be instrumental in operationalizing innovative solutions for our pharmaceutical, biotech, and science education customers. Your deep expertise in MLOps and cloud data platforms, especially Snowflake (or similar cloud-based approaches) and advanced AI capabilities, will be key to building scalable models that streamline purchasing, optimize supply chains, and power cutting-edge analytics.

Reporting to the Engineering Manager, Platform Data Science and Artificial Intelligence, you will bring significant machine learning deployment experience to help us build robust, production-ready models.

Are you an experienced ML Engineer with a track record of successfully taking models from development to reliable production deployment at scale? Are you adept at leveraging modern data warehouses and their integrated AI functionalities, particularly Snowflake Cortex, LLMs, Model Registry, or similar platforms? Do you thrive in autonomous environments, enjoy translating complex requirements into tangible, deployed solutions, and are passionate about using data to accelerate scientific discovery? If so, this position is an excellent opportunity.

Please note: This is a senior-level position requiring significant production ML experience. H1B visa sponsorship is unavailable at this time.

How You Will Contribute

• Lead the design, implementation, and management of robust, automated MLOps pipelines for continuous integration, delivery, deployment, and monitoring of ML models in production.
• Heavily leverage Snowflake's AI ecosystem, including Cortex AI & ML functions, LLMs, Model Registry, and Snowpark/data pipelines, to build, deploy, and manage models efficiently and scalably.
• Develop and own ML models end-to-end - from conception and training through to production deployment, monitoring, and lifecycle management.
• Partner with product, engineering, and business stakeholders to understand requirements and deploy ML models for use cases like product classification, recommendations, marketing optimization, and supply chain management.
• Establish and champion best practices for production ML engineering, ensuring reliability, scalability, and maintainability of deployed models and infrastructure.
• Define, implement, and track key performance metrics to evaluate model effectiveness, operational health, and business impact post-deployment.
• Explore and implement integrations using tools like Cortex Analyst and Agent AI to connect ML models with external systems (e.g., Slack, Teams).
• Communicate complex technical concepts and the status of deployed systems clearly to both technical and non-technical audiences.

What You Bring to the Team

• 3+ years of hands-on experience designing, building, and critically, deploying, monitoring, and managing machine learning models within production environments.
• Proven experience in implementing MLOps best practices and contributing to ML infrastructure for reliable, repeatable model lifecycle management (delivery, release, versioning, monitoring) in complex settings. This includes practical application of CI/CD principles for ML, hands-on experience with deployment strategies (such as blue/green or canary releases), implementing automated quality gates, establishing model monitoring, and integrating human check/review processes where appropriate.
• Experience with at least one of the following cloud-based data warehousing and AI platforms.
  • Snowflake. Demonstrable expertise in several of the following Snowflake features is strongly preferred:
    • Snowflake Cortex AI & ML Functions
    • Working with Large Language Models (LLMs) within Snowflake
    • Snowflake Model Registry for model versioning and management
    • Building and managing Snowpark / Snowflake data pipelines for ML workflows
    • Utilizing Cortex Analyst and Semantic Models
    • Experience with Cortex Agent AI for system integration
  • Experience with other platforms like Databricks or AWS (e.g., SageMaker) or others is beneficial, but strong Snowflake experience is the priority.
• Graduate degree (MS or PhD preferred) in Computer Science, Machine Learning, Data Science, Applied Mathematics, or a related quantitative field.
• Strong theoretical foundation and practical expertise in relevant ML areas (e.g., NLP/NER, classification, regression, clustering, recommendation systems, time series forecasting, optimization).
• Proficiency in Python, SQL, and Git is essential.
• Experience translating complex analytical problems into robust, scalable, production-ready solutions.
• Excellent communication skills, capable of explaining technical details and system performance to diverse audiences.
• Familiarity with life science lab operations or the pharmaceutical/biotech industry is a plus.
• Intellectual curiosity, strong problem-solving skills, and self-motivation to innovate in a fast-paced environment.

We provide a competitive set of benefits including but not limited to a hybrid - office/remote work option, health benefits, discretionary time off, parental leave, competitive salary and equity, and Thursday company lunches.

We are an equal opportunity employer and building a diverse team is our top priority. At Labviva, we celebrate all. Help us build an inclusive community that will transform the life sciences industry. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics as outlined by federal, state or local laws, regulations, or ordinances.