Applied AI / Machine Learning Engineer to design, build, and deploy practical AI-powered solutions that solve real-world problems. This role focuses on applying modern ML and GenAI techniques in production systems - from experimentation and prototyping through deployment, evaluation, and iteration. You'll work closely with engineers, designers, and product stakeholders to turn ambiguous problems into scalable, reliable AI-driven capabilities.
This is a hands-on engineering role for someone who enjoys shipping, learning quickly, and balancing technical rigor with real-world constraints.
What you'll be doing:- Design, develop, and deploy machine learning and AI-powered features into production systems
- Apply supervised, unsupervised, and deep learning techniques to structured and unstructured data
- Build and evaluate models for tasks such as classification, ranking, prediction, NLP, or anomaly detection
- Develop and integrate GenAI solutions (e.g., LLM-based workflows, retrieval-augmented generation, agents)
- Translate business and user needs into ML problem statements, metrics, and experiments
- Implement data pipelines and feature engineering workflows to support model training and inference
- Evaluate model performance, bias, drift, and reliability; iterate based on results
- Collaborate with software engineers to integrate models into APIs, services, and user-facing applications
- Contribute to architecture decisions around model serving, scalability, and cost optimization
- Document approaches, assumptions, and tradeoffs to support maintainability and knowledge sharing
What you'll bring:- 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 (e.g., PyTorch, TensorFlow, scikit-learn)
- Experience working with large language models, embeddings, and prompt-driven systems
- Familiarity with data processing tools and workflows (e.g., Pandas, SQL, Spark, or similar)
- Understanding of software engineering best practices (version control, testing, 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 working 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
Location: Hybrid/Remote. Candidates
must be located in the DMV area (DC, Maryland, Virginia) and able to participate with in-office collaboration.
Requirements:- 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.
Benefits:- Fully remote
- Annual stipend
- Comprehensive Benefits Package
- Company Match 401(k) plan
- Flexible PTO, Paid Holidays
Compensation:At Oddball, it's important each employee is compensated competitively and fairly. In alignment with state legal requirements. A range for the included position is listed below. Be advised, actual offer details are determined by job category, job location, and candidate skill level.
United States Wage Range: $150,000 - $200,000
