Lead AI Research Engineer

AVEVA•New York, MA

1d•Hybrid

About The Position

AVEVA is creating software trusted by over 90% of leading industrial companies. This pay range represents the minimum and maximum compensation that the position offers, and final compensation can vary within the range depending on work location, job experience, skills, and relevant educational attainment and/or training. We are seeking an experienced AI technologist to join our AI Investigation and Incubation team. This is a hands-on engineering lead role, focused on researching, prototyping, and validating emerging AI technologies to drive innovation and real-world use cases. The ideal candidate will have a passion for both exploring new frontiers in AI and turning AI research into working systems with expertise making architectural trade-offs, and proving feasibility through code, experiments, and deployable prototypes. A strong technical foundation with experience working at the intersection of AI research and incubation is critical for this role.

Requirements

10+ years of experience in AI research and development, ML engineering, or equivalent industry experience with at least 3 years in a technical lead position
Bachelor's degree in Computer Science, AI/ML, Engineering or a related technical field; advanced degree preferred
Proven track record leading and delivering large-scale technical investigations or complex AI cross-functional initiatives with measurable outcomes
Expertise in Python and deep experience with deep learning frameworks (e.g., Jax, TensorFlow, PyTorch) and state-of-the-art ML techniques (building, training, evaluating, deploying ML models)
Practical experience with modern AI paradigms such as: world models, foundation models, and multi-modal language models; agent-based systems and orchestration; and context retrieval and augmentation techniques
Exceptional communication and presentation skills; can articulate complex technical concepts to both technical and non-technical audiences, including senior leadership
Ability to connect AI capabilities to practical industrial or enterprise use cases

Nice To Haves

Exposure to AI governance, security, or compliance considerations
Experience deploying ML models in cloud environments (Azure preferred, AWS acceptable)
Familiarity with MLOps practices (model versioning, evaluation, monitoring, iteration)
Experience working with non-ideal, real-world data rather than curated research datasets
Exposure to industrial, IoT, manufacturing, energy, or asset-intensive domains
Experience working in both enterprise and start up environments

Responsibilities

Research and evaluate emerging AI technologies with a clear focus on practical applicability and deployability
Investigate, develop, fine-tune, evaluate, and benchmark AI/ML models
Design, build, and iterate on working prototypes, proof-of-concepts, and pilots
Assess AI approaches for scalability, reliability, cost, security, and operational feasibility
Make and document AI investigation and architectural decisions related to model deployment and integration
Drive technical and scientific publications on AI research
Collaborate closely with cross-functional teams to ensure AI proofs-of-concept, prototypes, and pilots can transition to later stage development and/or downstream products
Clearly document findings and present actionable recommendations to technical and non-technical stakeholders
Mentor and coach junior team members