Generative AI & Machine Learning Engineer with Security Clearance

About the role

You will be responsible for supporting product development efforts that range from generative AI and machine learning application development and deployment to model development and monitoring, ML management and DevOps. You will be a contributing member of a Software Engineering team that supports production applications and also helping to develop new features and models. The role will interface with internal and external stakeholders and provide continuity of technical and data-exploration expertise to ensure we are delivering a workable solution that meets the customer requirements and technical capabilities.

Responsibilities

• Experiment and Develop: Drive the end-to-end model development lifecycle, championing best practices to ensure reproducible research and well-managed software delivery.
• Collaborate: Work on a collaborative cross-functional team, sharing information, valuing diverse ideas, and partnering effectively with colleagues across the globe. Elevate and mentor teammates. Work closely with product teams to see your work integrated and deployed into production environments.
• Deliver: With a sense of urgency and the desire to work in a fast-paced, dynamic environment, translate complex business problems into projects with clearly defined scope. Our problems are complex; our solutions are right-sized. Be accountable for timely, well-managed deliverables.
• Innovate: Be empowered to try new approaches and learn new technologies. Foster innovative ideas to solve real-world challenges. Iterate on improvement rapidly with a mindset for failing fast and learning continuously from data.
• Inspire: Be a proactive communicator who is excited to share your work. Be articulate and compelling in describing ideas to both technical and non-technical audiences. Help lead the way in the adoption of AI across the enterprise.

Requirements

• You're a good fit for the role of Generative AI & Machine Learning Engineer if you have:
• A Master’s or Bachelor’s in a relevant discipline. Relevant experience will be considered in lieu of a degree.
• Proficiency in Python.
• At least 3+ years practical, relevant experience building AI/ML products and applications and recent demonstratable experience using Generative AI technologies such as RAG patterns, ReAct, LangChain etc for performing document summarization, knowledge graphs, information extraction, or analysis.
• Solid software engineering skills and experience.
• Experience as a technical leader, leading aspects of the following: aiding in the ideation with product stakeholders, comfort in dealing with uncertainty and ambiguity in problem statements and paths to success, breaking down complex problems into tractable components with iterative improvements, formulating research and development plans, coordinating and working with others, communication of progress and plans with varied stakeholders.
• Hands-on coding experience on AI/ML projects in current role and experience in designing, developing, and implementing machine learning models and algorithms.
• Ability to obtain and maintain a U.S. national security clearance.
• U.S. Citizenship essential to comply with government contract/agency or department of Federal Government requirements.

Preferred Skills and Tools

• 6+ years practical experience using AI and ML to solve diverse and/or ambiguous problems in academia or industry.
• Experience with AI Agent frameworks and patterns.
• Familiarity with common NLP use cases such as chatbot development and information retrieval (RAG), language translation, NER, summarization and topic modeling.
• Familiarity with LLM training and efficient finetuning (PEFT, LoRA, Quantization).
• Experience with NLP/CV libraries such as PyTorch, TensorFlow, Scikit-learn, spaCy, HuggingFace Transformers/Diffusers, OpenAI, LangChain, Semantic Kernel & OpenCV.
• Experience using Cloud solutions (AWS, Azure, etc.) for building and deploying applications.
• Experience in a fast-paced, agile environment managing uncertainty and ambiguity.
• Proficiency in Python and experience delivering minimum viable products in a large enterprise environment.
• Experience developing libraries and APIs for others to use.
• Outstanding communication and data-driven decision-making collaboration with Product + Business Stakeholders.
• Diverse experiences across problem spaces, companies and cultures.