Applied AI/Machine Learning Engineer

Join Oddball to design, build, and deploy applied AI and machine learning capabilities that move from experimentation to real production impact. This hybrid role in McLean, VA supports modern ML and GenAI workflows across model development, evaluation, and iteration, with cross-functional collaboration to integrate AI into user-facing systems.

What you’ll do

• Design, develop, and deploy machine learning and AI-powered features into production systems
• Use supervised, unsupervised, and deep learning approaches with structured and unstructured data
• Build and evaluate models for tasks including classification, ranking, prediction, NLP, and anomaly detection
• Develop and integrate GenAI solutions such as LLM-based workflows, retrieval-augmented generation, and agents
• Translate business and user needs into ML problem statements, metrics, and experiments
• Implement data pipelines and feature engineering workflows for both training and inference
• Evaluate performance while considering bias, drift, and reliability, then iterate based on results
• Collaborate with software engineers to integrate models into APIs, services, and user-facing applications
• Contribute to architecture decisions for model serving, scalability, and cost optimization
• Document approaches, assumptions, and tradeoffs to support maintainability and knowledge sharing

Skills and experience

• Strong foundation in machine learning concepts, including model selection, training, validation, and evaluation
• Experience building and deploying ML models in real-world applications
• Proficiency in Python and common ML libraries such as PyTorch, TensorFlow, and scikit-learn
• Experience working with large language models, embeddings, and prompt-driven systems
• Familiarity with data processing workflows and tools such as Pandas, SQL, Spark, or similar
• Understanding of software engineering best practices including version control, testing, and code reviews
• Ability to reason about tradeoffs between accuracy, latency, cost, and maintainability
• Strong communication skills and comfort working in cross-functional teams
• Performs other related duties as assigned

Bonus if you have

• Experience in innovation, R&D, labs, or exploratory engineering teams
• Experience deploying models to cloud platforms and managing inference at scale
• Familiarity with MLOps practices such as model monitoring, CI/CD for ML, and experiment tracking
• Experience contributing to architectural discussions or technical strategy

Technologies you may work with

Python, PyTorch, TensorFlow, scikit-learn, LLM-based workflows, retrieval-augmented generation, Pandas, SQL, Spark, APIs, and services.

Location

• Hybrid/Remote, with occasional in-office collaboration
• Candidates must be located in the DMV area (DC, Maryland, Virginia)
• Work Location: Hybrid remote in McLean, VA 22102

Authorization and eligibility

Applicants must be authorized to work in the United States. In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance.

Compensation

United States wage range: $150,000 - $200,000 per year. Job type: Full-time.

Benefits

• Annual stipend
• Comprehensive Benefits Package
• Company Match 401(k) plan
• Flexible PTO and Paid Holidays

Additional benefits listed

• 401(k) and 401(k) matching
• Dental, vision, and health insurance
• Health savings account
• Life insurance
• Paid time off and parental leave
• Professional development assistance
• Referral program
• Retirement plan
• Flexible schedule
• Flexible spending account