Job Title: Machine Learning Engineer
Department : Labs
Work Location: Chicago
Reports To: Head of Labs
Who We Are:
Valor Equity Partners is a different kind of private investment firm. We invest in technology and technology-enabled companies that innovate and disrupt existing industries — from biosciences to transportation to food to health and wellness.
Our mission is to invest in and work side by side with companies that make the world a better place. These companies include SpaceX, Anduril, GoPuff, HackerOne, Cloud9, and others. We’ve had the honor of serving some of the world’s greatest entrepreneurs and companies.
Our values are core to all we do. These values are excellence, humility, integrity, and responsibility.
Valor means that we:
- Strive forexcellence in everything we do;
- Maintain ourhumility and mutual respect no matter what circumstances we encounter;
- Insist upon the highest level ofintegrity in our interactions and in the logic of our investment process; and
- Demonstrateresponsibility and dedication to all of our constituents.
About the Team:
Labs is an internal team at Valor that builds software to support the Firm’s investment process. It comprises software, data, and machine learning engineers as well as data scientists with diverse backgrounds and levels of experience. The team’s mission is to build cutting edge software applications and data models that generate proprietary investment insights and provide the investment team with tools that augment the investment decision making process.
About the Role:
- Collaborate with data scientists and software engineers to build, deploy, monitor, and maintain ML models in production environments
- Lead the integration of ML workflows with CI/CD pipelines, ensuring consistent and seamless model versioning, testing, and rollout
- Create, design, and deploy ETL and ELT flows for consuming from disparate sources of 3rd party data for various machine learning applications
- Build tooling to monitor data pipelines and perform troubleshooting and debugging to identify and resolve data quality and performance issues
- Collaborate with data scientists, engineers, and other stakeholders in translating project requirements into technical specifications
- You will help shape the future of software engineering at Valor by bringing your ideas on improving and automating what we do and how we do it
We’re excited about candidates that have…
- 5+ years of machine learning, data science, software development, and/or similar experience, with significant contributions that you can talk to
- Exceptional coding skills in Python
- Additional skills in RESTFUL API design, especially Flask, Django, or FastAPI are good to have
- SQL skills and working knowledge of multiple database types
- Experience in ML Ops and deploying machine learning models
- Experience with modern cloud platforms (AWS, Azure, or GCP)
- Experience with NLP techniques (incl. SOTA LLMs)(good to have)
- Experience in DevOps for CI/CD and IaC (Infrastructure as Code)(good to have)
- Experience in Kubernetes clusters and GPU-based infrastructure
- Experience with Scala and Spark or PySpark(good to have)
- Modern data pipeline experience(good to have)
- Passion for machine learning while being mission-driven, hard-working, humble, intellectually curious, and most importantly, great team players
- Bias for execution and delivery. You know that what matters is delivering software that works every time
- Ability to assist in system design and the generation of key technical assumptions while encouraging solutions that respect existing infrastructure
- Willingness to be resourceful, flexible, and adaptable; no task is too big or too small
Our Tech Stack
- Frontend: React with Hooks, Material UI
- Backend: Python, Fast API
- Tooling: Google Cloud Platform
- Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt