AI​/ML Engineer III

AI/ML Engineer III

Utica-Rome NY Hybrid or Remote

Technergetics is looking for an AI/ML Engineer III to design, develop, and deploy advanced AI capabilities alongside a high-performing team of full-stack developers. This role centers on building production systems around foundation models, including agentic workflows, retrieval-augmented generation, and multimodal machine learning, for demanding government and commercial customers.

Contingent Position:
This position is contingent upon contract award and funding.

Salary Range: $125,000–$175,000 annually. The final offer depends on how many position qualifications the candidate meets, as well as education and experience. This is a full-time, exempt position.

• Candidates who are located within, or relocate to, a commutable distance of the Utica/Rome area can expect to be onsite 20% of their workweek, for access to company and AFRL (Air Force Research Lab) facilities, secure data, and customers. A relocation signing bonus may be available.
• Remote candidates outside a commutable distance to Utica/Rome will still be considered but may need to travel to the Utica/Rome area quarterly or more often, depending on company and client needs.
• This position also involves approximately 5%–10% travel to customer and client sites outside the Utica-Rome, NY area.

Due to the security clearance required for this position, only U.S. citizens are eligible to apply, per Executive Order 12968 (Access to Classified Information).

The successful candidate will work on one or more of our Machine Learning (ML) software products, with day-to-day activities that include:

• Leading the design, development, and deployment of multi-modal machine learning architectures, including models and algorithms, to solve complex mission and business problems
• Designing and building agentic systems on top of large language models for operational deployment
• Implementing retrieval-augmented generation pipelines that ground model outputs against authoritative data sources
• Defining and running evaluation for model and agent behavior in production
• Optimizing model inference for production and edge/DDIL (denied, degraded, intermittent, and limited bandwidth) deployment scenarios
• Applying AI assurance practices and documenting model limitations to support accreditation and customer review
• Integrating state-of-the-art machine learning libraries, foundation models, and agent frameworks into existing software applications
• Developing and maintaining data pipelines and supporting software for collecting, preprocessing, and transforming data for machine learning tasks
• Designing software solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by the product owner and other stakeholders in a production environment
• Leading, coaching, and mentoring junior data scientists, engineers, and other staff
• Contributing to phases of the software development life cycle, including functional analysis, technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support
• Participating in daily scrums and working with the scrum master and scrum team to organize and prioritize workload through story-pointing, supporting delivery timelines and priorities
• Collaborating with cross-functional teams to understand business requirements and translate them into machine learning solutions
• Performing unit testing and debugging to identify and fix software defects, and contributing to code reviews with constructive feedback to peers
• Staying current on new AI/ML approaches, frameworks, and industry trends
• Serving as an AI subject matter expert for small teams of researchers and engineers on advanced R&D projects funded by government and/or commercial customers, and contributing to or leading proposal writing for new opportunities within your area of expertise

This position generally requires a Master's degree from an accredited college or university in computer science, computer engineering, artificial intelligence, machine learning, or a closely related discipline. A Ph.D. in one of these fields is strongly preferred. A Bachelor's degree in one of these fields, combined with seven or more years of directly relevant professional experience, will be considered in lieu of a Master's degree.

• At minimum, three years of professional experience in machine learning or AI systems engineering, including at least one year building with large language models or other foundation models in a production setting
• Strong proficiency in Python, including asynchronous programming and modern packaging and dependency management
• Working knowledge of server-side development (API definitions, REST services, streaming and asynchronous services, etc.)
• Fluency with containerization and deployment frameworks such as Kubernetes or Docker, including GPU scheduling and…