<p><strong>About the Role</strong><br><br>Join Labviva as a <strong>Senior Machine Learning Engineer, Platform Data Science and AI</strong>.&nbsp; Reporting to the<strong> </strong>Engineering Manager, Platform Data Science and Artificial Intelligence, you will play a critical role for enhancing Labviva’s data integrations via APIs, ELTs, terraform as IaC, in different data-driven initiatives such as ML/AI models, BI, data science, data warehouse (Snowflake), and data engineering to improve functionality for our customers, including exciting challenges at the intersection of software engineering and data. This unique role is designed for a versatile engineer passionate about building end-to-end solutions, with a significant focus on data-centric systems. You will dedicate approximately <strong>50% of your time to backend development, 40% to data engineering tasks, and 10% to frontend development.</strong> This position represents a full-stack engineering role with focus on delivering, releasing, and deploying in a repeatable way different software components, with a very close evolution towards and deep involvement in data engineering practices.</p> <p>You will enhance Labviva’s data integrations via APIs, design and implement robust ETL/ELT processes, manage infrastructure using Terraform (IaC), and contribute to diverse data-driven initiatives including ML/AI model integration, Frontend React integrated with Business Intelligence (BI with Sisense platform), data science support, data warehousing (Snowflake), and core data engineering pipelines. Your primary goal will be to build and optimize systems capable of handling millions of data-rich records, integrating seamlessly with our Snowflake data warehouse and AWS-based infrastructure, ultimately improving functionality and providing a high-performance experience for our scientist and procurement users.</p> <p>This role is ideal for a software engineer who thrives on a holistic approach—from crafting user interfaces for BI and building APIs, to developing backend services, ensuring efficient data replication and delivery, and integrating with external systems. We're looking for someone detail-oriented, collaborative, and adept at balancing innovative feature development with system health, security, and maintainability. You should be eager to explore new technologies, drive system-wide improvements, particularly in support of ML/AI and data science initiatives and sophisticated data engineering pipelines, and possess a strong affinity for data challenges.</p> <p><em>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.<br></em></p> <p><strong>How You Will Contribute</strong></p> <ul> <li><strong>Data Engineering &amp; Architecture (Approx. 40%):</strong></li> <ul> <li>Architect, implement, and optimize scalable data harmonization and ETL/ELT solutions using modern tooling and best practices.</li> <li>Collaborate closely with Data Science and AI teams to ensure smooth integration of ML models and analytics into the platform.</li> <li>Design and manage data flows supporting data ingestion, transformation, and warehousing within Snowflake.</li> <li>Manage and provision infrastructure using Terraform (IaC) within our AWS environment.</li> </ul> <li><strong>Backend Development (Approx. 50%):</strong></li> <ul> <li>Develop robust and scalable backend services and APIs using Node.js (Nest.js, TypeORM) and Python to support data pipelines and application features.</li> <li>Ensure efficient and reliable delivery of data to the platform and downstream systems.</li> <li>Contribute to architectural decisions and future technology planning, evaluating tools and frameworks for performance and reliability.</li> </ul> <li><strong>Frontend Development (Approx. 10%):</strong></li> <ul> <li>Design and integrate responsive and intuitive frontend features using React, Typescript, and related libraries to our BI platform in Sisense.</li> <li>Integrate frontend components with backend APIs and data sources.</li> <li>Develop interfaces for internal tools and BI platforms (like Sisense) to facilitate data exploration and model interaction.</li> </ul> <li><strong>Collaboration &amp; Mentorship:</strong></li> <ul> <li>Mentor, collaborate effectively with, and learn from fellow software engineers, ML engineers, data scientists, and other stakeholders across the company.</li> <li>Actively participate in code reviews, knowledge sharing sessions, and promote engineering best practices.</li> </ul> </ul> <p><strong>What You Bring to the Team</strong></p> <ul> <li>Proven track record in taking large, complex software and/or data projects from concept through to successful implementation.</li> <li>Experience acting as a technical or functional Subject Matter Expert (SME), guiding project direction and making key architectural decisions.</li> <li>Strong analytical and problem-solving skills, particularly when dealing with high-complexity technical challenges or ambiguous requirements.</li> <li>Fluency in several of the following technologies:</li> <ul> <li><strong>Frontend:</strong> React, Typescript</li> <li><strong>Backend:</strong> Node.js (Nest.js, TypeORM preferred), Python</li> <li><strong>Infrastructure:</strong> AWS (core services like EC2, S3, RDS, Lambda), Kubernetes, Docker, Terraform, Kafka (or similar messaging systems)</li> <li><strong>Databases:</strong> Relational databases (e.g., PostgreSQL/AWS Aurora), NoSQL databases</li> <li><strong>Data Warehouse:</strong> Significant hands-on experience with cloud-based data warehousing solutions. <strong>Snowflake experience is preferred.</strong> Familiarity with Databricks, AWS data services (e.g., Redshift, Glue, SageMaker), <strong>or similar platforms is valuable</strong>.</li> <li><strong>Search:</strong> Experience with Elasticsearch or other search technologies (including performance tuning, particularly for catalog search) <strong>is a significant plus</strong>.</li> </ul> <li>Comfortable working across the full stack, from database, APIs and infrastructure up to the data warehouse.</li> <li>Demonstrable hands-on experience building and maintaining data ETL/ELT pipelines.</li> <li><strong>Highly Desirable:</strong> Experience integrating with machine learning workflows or supporting ML model deployment.</li> <li>Experience in e-commerce or procurement platforms <strong>is a plus</strong>.</li> <li>Excellent communication skills and a collaborative spirit, committed to fostering an inclusive and diverse team environment.</li> </ul> <p><strong>About the Company</strong></p> <p>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.<br><br>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.</p> <p>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.</p> <p>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.</p><div class="content-conclusion"><div id="apply"></div></div>