Applied AI/Machine Learning Engineer

Oddball; McLean (VA); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Fully remote option

Annual stipend

Comprehensive Benefits Package

Company Match 401(k) plan

Flexible PTO and paid holidays

Dental insurance

Flexible schedule

Flexible spending account

Health insurance

Health savings account

Life insurance

Paid time off

Parental leave

Professional development assistance

Referral program

Retirement plan

Vision insurance

401(k) and 401(k) matching

Job summary

Oddball is seeking an Applied AI/Machine Learning Engineer to design, develop, and deploy machine learning and GenAI solutions in production systems. The hybrid role is based in McLean, VA, with occasional in-office collaboration between applied modeling and software engineering teams.

You will build and evaluate models across classification, ranking, prediction, NLP, and anomaly detection, translate business needs into ML problems, and design data pipelines for training and inference.

Qualifications

• Strong foundation in machine learning concepts including model selection, training, validation, and evaluation.
• Experience building and deploying ML models for real-world applications.
• Proficiency in Python and ML libraries such as PyTorch, TensorFlow, and scikit-learn.
• Experience with large language models, embeddings, and prompt-driven systems.

Responsibilities

• Design, develop, and deploy machine learning and AI-powered features into production systems.
• Apply supervised, unsupervised, and deep learning approaches across 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 training and inference.
• Evaluate model performance, bias, drift, and reliability, then iterate based on results.
• Collaborate with software engineers to integrate models into APIs, services, and user-facing applications.
• Participate in architecture decisions related to model serving, scalability, and cost optimization.
• Document approaches, assumptions, and tradeoffs for maintainability.

Skills

ML concepts

Model deployment

Cross-functional collaboration

Evaluation

Project scoping

Communication

Tools

Python

PyTorch

TensorFlow

scikit-learn

Pandas

SQL

Spark

Job description

Oddball is building production-ready AI capabilities and is seeking an Applied AI/Machine Learning Engineer to design, develop, and deploy machine learning and GenAI solutions. The work spans experimentation and prototyping through evaluation, iteration, and integration into live systems, with a focus on reliability and measurable impact.

This hybrid role is based in the McLean, VA area, supporting occasional in-office collaboration with a team that bridges applied modeling and software engineering.

What you’ll do

• Design, develop, and deploy machine learning and AI-powered features into production systems
• Apply supervised, unsupervised, and deep learning approaches across 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 that support both training and inference
• Evaluate model performance, bias, drift, and reliability, then iterate based on results
• Collaborate with software engineers to integrate models into APIs, services, and user-facing applications
• Participate in architecture decisions related to model serving, scalability, and cost optimization
• Document approaches, assumptions, and tradeoffs for maintainability and knowledge sharing
• Perform other related duties as assigned

Required skills

• Strong foundation in machine learning concepts, including model selection, training, validation, and evaluation
• Experience building and deploying ML models for 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 tools and workflows including Pandas, SQL, Spark, or similar
• Understanding of software engineering best practices such as version control, testing, and code reviews
• Ability to weigh tradeoffs between accuracy, latency, cost, and maintainability
• Strong communication skills and comfort working in cross-functional teams
• Authorization to work in the United States; some roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or security clearance

Technologies you’ll work with

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

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 including model monitoring, CI/CD for ML, and experiment tracking
• Experience contributing to architectural discussions or technical strategy

Compensation and employment details

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

Location

• Hybrid remote in McLean, VA 22102
• Must be located in the DMV area (DC, Maryland, Virginia) and able to participate in occasional in-office collaboration

Benefits

• Fully remote option
• Annual stipend
• Comprehensive Benefits Package
• Company Match 401(k) plan
• Flexible PTO and paid holidays
• Dental insurance
• Flexible schedule
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Parental leave
• Professional development assistance
• Referral program
• Retirement plan
• Vision insurance
• 401(k) and 401(k) matching