Note: The job is a remote job and is open to candidates in USA. Pantheon Data is seeking a Senior Machine Learning Engineer to build production-oriented Artificial Intelligence and Intelligent Document Processing systems. The role involves developing Python services and data pipelines, integrating and evaluating machine learning and large language models, deploying cloud or containerized services, and improving document understanding, retrieval, monitoring, and system reliability.
Responsibilities
- Design, implement, and maintain ML/AI software components for IDP and Generative AI systems
- Build data pipelines for unstructured and semi-structured data, including document ingestion, extraction, cleaning, enrichment, validation, and storage
- Develop and evaluate NLP, OCR, computer vision, embedding, retrieval, and LLM-based approaches for document understanding use cases
- Create APIs, internal tools, review interfaces, dashboards, or validation workflows that allow engineers and users to inspect, correct, and trust system output
- Contribute production-quality code with clear structure, tests, logging, error handling, and documentation
- Deploy and support ML/AI services in cloud or containerized environments, including model serving, batch processing, and workflow automation
- Design evaluation approaches for extraction quality, retrieval quality, model behavior, hallucination risk, and end-to-end system performance
- Troubleshoot system behavior across model output, data quality, retrieval, schema design, infrastructure, latency, cost, and user workflow issues
- Mentor other engineers and help raise the technical quality of the team
- Communicate clearly with both technical and non-technical stakeholders, including project managers, customers, and executive leadership
Skills
- Bachelor's degree in Computer Science, Engineering, or a related technical field from an ABET accredited university
- 5+ years of professional hands-on experience in machine learning engineering, AI engineering, data science engineering, or a closely related software engineering role. Plus an additional 5 years of experience in technology and software engineering
- Demonstrated experience building AI/ML systems beyond notebooks, prototypes, or demos. Candidates should have shipped or supported pipelines, services, APIs, inference endpoints, evaluation harnesses, or production-facing tools
- Strong Python engineering experience, including readable, maintainable code; debugging; testing; packaging; and integration with other systems
- Hands-on experience with NLP, OCR, computer vision, LLMs, embeddings, semantic search, RAG, or other document-understanding techniques
- Experience working with unstructured or semi-structured data such as PDFs, scanned documents, forms, tables, images, logs, contracts, technical manuals, or engineering documentation
- Ability to design and reason about end-to-end data flow: source data, preprocessing, transformation, model/inference step, persistence, API/service boundary, evaluation, and user-facing output
- Familiarity with common ML frameworks and tooling such as PyTorch, TensorFlow, scikit-learn, Hugging Face, MLflow, or similar technologies
- Experience with databases and data stores, including SQL and at least one relational or non-relational data platform
- Experience using Git-based development workflows, code review, issue tracking, and team-based software delivery practices
- Clear written and verbal communication skills, including the ability to explain technical tradeoffs, limitations, and failure modes
- Ability to work effectively remotely in cross-functional teams
- Ability to meet deadlines and produce quality work
- Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint
- Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Secret Clearance is required for continued employment
- Direct experience with Intelligent Document Processing, document AI, OCR pipelines, table extraction, form extraction, layout-aware processing, or evidence-grounded retrieval
- Experience building, deploying, or operating LLM-backed systems, including inference serving, prompt/version management, model evaluation, retrieval, observability, or cost/latency management
- Experience with cloud platforms such as AWS or Azure, including storage, compute, serverless, networking basics, IAM, monitoring, or managed ML/AI services
- Experience with containers and deployment workflows, including Docker, Kubernetes, CI/CD pipelines, automated tests, and environment promotion
- Experience building user-facing or internal tools such as validation interfaces, review workflows, dashboards, admin tools, or lightweight full-stack applications
- Experience with data engineering tools such as pandas, NumPy, Spark/PySpark, Databricks, Airflow, or similar workflow/data platforms
- Experience with observability, performance profiling, or debugging tools such as Grafana, CloudWatch, TensorBoard, tracing tools, GPU profiling tools, or application logs
- Experience with evaluation design, benchmarking, reproducibility, statistical analysis, error analysis, or human-in-the-loop validation
- Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, Physics, Statistics, Data Science, or another technical discipline. Equivalent professional experience will also be considered
- Demonstrated ability to mentor junior developers or contribute to team technical direction
Benefits
- Remote work from Reston, VA, with flexibility and collaboration whether working in person or remotely
- SmartBenefits through the Washington Metro Area Transportation Authority, allowing employees to specify an amount of pre-tax wages to be paid directly to their SmarTrip account
- In some cases, tuition assistance may be available for continuing education expenses and certifications related to the employee's position
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