HERE is looking for a highly skilled and visionary
Lead AI/ML Engineer
to join our
Technology Innovation Lab
a team dedicated to pushing the boundaries of whats possible with AI. You will lead the development of intelligent systems powered by
Generative AI
,
Agentic AI
, and
Classical Machine Learning
, driving innovation across real-world applications.
This role demands both hands-on technical depth
and strategic thinking
. You will architect intelligent workflows involving autonomous agents
, build scalable ML systems, and integrate next-gen AI capabilities into prototypes that shape the future of HERE
Key Responsibilities
-
Architect and build AI-first systems using Large Language Models (LLMs)
, Autonomous Multi-Agent Frameworks
, and Classical ML models
.
-
Lead development of Agentic AI solutions
, including task orchestration, memory management, tool use, and human-agent feedback loops.
-
Drive end-to-end GenAI applications including text generation, summarization, image synthesis
, code generation, and multi-modal interfaces.
-
Mentor a team of data scientists and engineers; define best practices in prompt engineering
, agent collaboration
, and evaluation frameworks
.
-
Collaborate with cross-functional teams to transform domain problems into scalable AI solutions.
-
Stay current with and evaluate emerging tools, models, and open-source projects in LLMs, LangGraph, CrewAI, AutoGen
, and related ecosystems.
-
Identify opportunities for innovation and contribute to publications, patents, or internal IP generation.
- Design experiments and stay up-to-date with industry inventions in AI/ML (focus on LLM, NLP, Computer vision), quantum computing( good to have), location
intelligence, distributed computing, LiDAR and drone processing, 3D modeling and AR/VR(good to have), emphasizing the engineering aspect of technological advancements. Relevant experience in deep learning, LLM based models, neural network, transformers and diffusion model with good coding and mathematical experience. -
Ensure solutions are scalable, explainable, and aligned with responsible AI principles.
- Work with the Manager to Identify and Define lead KPIs related to effective assessment of performance at individual level and impact assessment of innovation implementation at business unit level.
Who are you?
-
Master s or Ph.D.
in Computer Science, Mathematics, Machine Learning, AI
, or other related quantitative fields.
-
Demonstrated expertise in Agentic AI systems
experience building, deploying, or designing autonomous multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen, OpenAgents
).
-
Ability to design agents with tool use, memory, planning, reflection, and task decomposition
capabilities.
-
Exposure to Mission Control Platforms (MCPs) or centralized agent orchestration is a plus.
-
Strong applied knowledge in Machine Learning, Deep Learning, and Computer Vision
, including architectures such as CNNs, RNNs, GANs, Transformers
, and Diffusion Models
.
-
Practical experience with Large Language Models (LLMs)
such as GPT-3/4, Claude, Mistral, LLaMA
, including techniques like prompt engineering
, fine-tuning
, or embedding-based retrieval
.
-
Strong programming background in Python
(required), and working knowledge of C++
, Java
, or similar languages for scalable ML systems and software implementation.
-
Hands-on exposure to distributed systems
, high-performance computing
, or big data tools
like Spark, Ray, Hadoop
, or PySpark
.
-
Previous participation in internships, research collaborations, or volunteering
with professionals in AI/ML domains, showing the ability to apply academic learning to real-world problems.
-
Demonstrated ability to innovate in emerging fields with a creative, first-principles approach
to problem-solving.
-
Curiosity and openness to explore future-facing domains like Quantum AI
, TinyML
, Edge Intelligence
, or 3D Spatial Modeling
.
