Applied Machine Learning Engineer
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About Us
Syntracts is an AI-powered legal-tech startup on a mission to deliver on the unfulfilled promise of legal AI, reshaping how top firms turn their most valuable asset, their contracts, into structured, actionable intelligence.
Forget prompt engineering and wrapping third-party APIs. We’re building the foundational layer for legal data. With backing from top VCs in NYC, SF, and Boston, our proprietary platform uses hundreds of fine-tuned small language models to structure complex legal documents with unparalleled accuracy. It’s built for the enterprise: secure, scalable, and deployable entirely on-premises.
This is a unique opportunity to join as one of our early team members and help shape not just our operations, but also our culture, processes, and trajectory.
The Role
As an Applied Machine Learning Engineer at Syntracts, you’ll play a critical role in building the data and ML infrastructure that powers our next generation of intelligent legal products. Partnering directly with our Applied ML Architect, you’ll design and implement a world-class Data Intelligence Platform that enables rapid model development, seamless deployment, and enterprise-scale performance. From architecting pipelines and orchestration layers to building integrations that transform raw data into actionable intelligence, your work will define how we leverage AI and traditional ETL across the organization.
This is a rare opportunity to help build a platform from the ground up. You’ll operate at the intersection of data engineering and MLOps, owning the systems that make ML possible in production. Collaborating closely with researchers, analysts, and engineers, you’ll have autonomy and influence over key architecture decisions while shaping the backbone of our data-driven future.
This role reports directly to the VP of Engineering, and is fully remote, with occasional travel to New York City for team events.
Responsibilities
You will be responsible for architecting and developing core platform capabilities, with a focus on:
Platform Development: Partner with the AML team to design, build, and support a cutting-edge Data Intelligence Platform that serves as the foundation for model building and deployment across the organization.
Pipeline Ownership: Take ownership of existing data pipelines, identifying opportunities for optimization, reliability improvements, and performance enhancements. Ensure data flows are robust, scalable, and meet the needs of the platform.
System Integration: Build and maintain robust integrations across enterprise systems, with particular focus on AI Gateway implementations and orchestration layers that enable seamless data flow and model deployment.
Collaborative Development: Work alongside Analysts, researchers, and engineering team members to review designs, provide technical input, and ensure solutions align with stakeholder requirements and business objectives.
AI/ML Infrastructure Support: Analyze data patterns and evaluate AI opportunities as they directly impact existing data pipelines and platform capabilities, implementing solutions that enhance our ML infrastructure.
Experience & Skills
5+ years of experience in machine learning engineering, data engineering, or related software development roles
Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, or similar)
Hands-on experience building and deploying machine learning models in production environments
Proficiency with data pipeline tools and orchestration frameworks (Apache Airflow, Prefect, Dagster, or similar)
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
Solid understanding of ML operations practices, including model versioning, monitoring, and CI/CD
Strong SQL skills and experience working with both relational and NoSQL databases
Excellent problem-solving abilities and experience with data analysis and statistical methods
Strong communication skills with ability to explain technical concepts to diverse audiences
Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field (or equivalent practical experience)
Bonus Points if…
Experience with unified data analytics platforms such as Databricks, Snowflake, or similar lakehouse architectures
Familiarity with Apache Spark and distributed computing frameworks
Experience with LLM applications and AI gateway solutions (LangChain, LlamaIndex, etc.)
Knowledge of vector databases and embedding-based retrieval systems
Familiarity with enterprise integration patterns and API design
Experience with real-time data processing and streaming platforms (Kafka, Kinesis, etc.)
Background in MLOps tools and platforms (MLflow, Weights & Biases, Kubeflow, etc.)
Contributions to open-source ML projects
Experience working in cross-functional teams with product managers and domain experts
Knowledge of data governance, privacy, and security best practices
Previous experience scaling ML systems in production environments
Why Join Us
Be a true partner in shaping a company from day one
Competitive salary + meaningful equity
Direct collaboration with experienced founders and mission-driven team
Salary Range: Competitive salary plus a performance bonus and equity, commensurate with experience
Benefits:
Health, dental, and vision insurance
Flexible PTO and remote work options
We aim to offer a total compensation package that is competitive to companies at our same stage and reflects the value you bring to the team.
How to Apply
Excited about this opportunity? We’d love to hear from you! Please email your resume to careers@syntracts.com.
Equal Employment Opportunity
Syntracts is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, or any other characteristic protected by law. We believe diverse teams build stronger companies and strongly encourage candidates from all backgrounds to apply.