ComponentWise has spent more than two decades delivering mission-critical technology for commercial clients and federal agencies, including more than 10 years supporting USCIS digital transformation initiatives.
Our teams build and modernize systems that process millions of immigration cases annually. The work is technically complex, highly collaborative, and directly tied to services people rely on every day. Behind every transaction is a person pursuing legal immigration: a family seeking reunification, a professional building a career, or someone taking the defining step toward citizenship. The software we build does not just process cases. It moves lives forward.
We are a minority-owned small business that values engineering craftsmanship, long-term ownership, and sustainable delivery. Our employees stay because they work on meaningful problems alongside experienced teammates who care deeply about quality. Our very high retention rate is not a talking point. It is what happens when people are proud of what they build and who they build it with.
The Role
We are hiring across multiple experience levels, from early-career data scientists to experienced senior contributors. Responsibilities, technical scope, and ownership will scale based on experience and demonstrated capability.
You will join a collaborative data science team responsible to build AI/ML solutions for one of the federal government's largest case management ecosystems. The platform includes more than 100 production microservices, petabytes of data and a broad network of integrations across federal agencies and interagency partners.
Depending on experience level, you may contribute to existing machine learning models, develop new models, add model monitoring, modernize existing solutions or lead innovation using latest models, cloud services and GenAI technology.
This role is ideal for data scientists who enjoy solving complex technical problems, learning continuously, and building solutions that operate at large scale.
What You'll Do
- Contribute to the development and maintenance of existing machine learning models and their associated Python libraries.
- Build new models using frameworks and libraries like PyTorch, Transformers, XGBoost, etc.
- Perform Exploratory Data Analysis (EDA) on big data using Python and Spark.
- Create solutions that use and ensemble to custom models and integrate with AWS cloud AI/ML services like Textract, Comprehend and Bedrock.
- Develop automation for model monitoring for new and existing solutions.
- Write and maintain unit, integration, and end-to-end tests for Python libraries.
- Participate in monitoring, troubleshooting, and operational support appropriate to experience level
- Collaborate with data engineers, developers, product owners, and government stakeholders to deliver mission-critical capabilities
- Contribute to secure, maintainable, and well-tested software throughout the development lifecycle
Core Technologies
- Python, Spark
- PyTorch, Sckit-learn, Transformer, NLP, NER
- LLM, Foundation models, GenAI, Claude
- Databricks, AWS
- ANSI SQL, Spark SQL, SQL, Databricks Delta
- Databricks MLflow, model registry
- Kubernetes, Helm, ArgoCD
- GitHub Actions, Harness
- New Relic, Splunk
- Pytest, unittest
Core Qualifications
- Bachelor’s degree in data science or a related technical field, or equivalent practical experience
- Experience building machine learning models using Python or R
- Experience with data analysis using Python or R
- Hands on experience with SQL and data frames (Pandas, Spark, etc.).
- Understanding of data science fundamentals, machine learning lifecycle, deployment and monitoring best practices
- Strong communication and collaboration skills
- Ability to learn quickly and adapt to evolving technologies and mission needs
- US citizenship and ability to obtain and maintain DHS suitability
Additional Experience That's Helpful
- Building analytics solutions in Databricks
- Working with AWS services like S3, Bedrock, Textract, Comprehend, etc.
- Experience with event-driven systems asynchronous AI/ML systems
- Develop data-driven solutions in DataOps and MLOps processes
- Model monitoring in production and automated retraining
- Prompt engineering using latest foundation models
- Experience with text extraction, NER and NLP
How We Work
- Small collaborative teams with high ownership
- PR-based development and peer code review
- Automated testing and CI/CD by default
- Data scientists contribute to architecture and operational decisions
- Sustainable pace over hero culture
- Focus on maintainability, reliability, and long-term system health
Data scientists at all levels are encouraged to contribute ideas, grow their technical depth, and take on increasing ownership over time. We value curiosity, strong fundamentals, sound judgment, and a willingness to learn as much as prior experience with any specific technology.
Why Join Us
- Work on systems that operate at global scale
- Solve technically challenging distributed systems problems
- Collaborate with experienced engineers in a low-ego environment
- Build AI/ML solutions with measurable real-world impact
- Join a team with strong long-term retention and meaningful ownership opportunities
Our strongest hires have not always come with every skill on the list. What they shared was a strong data science foundation and the kind of intellectual curiosity that makes hard problems feel like opportunities. If that is how you think, we want to talk.
This position requires the ability to obtain and maintain a DHS suitability determination. US citizenship is required.
Pay: $80,000.00 - $150,000.00 per year
Work Location: Remote
