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LeadFull-timePythonAWSKubernetesMachine LearningPyTorchAIML
Salary Range
$153,000 - $207,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Tech Lead for Data, ML & AI Tools to join Kraken Utilities, a technology company focused on creating a smart, sustainable energy system. This role involves leading a high-impact team building AI-powered tools and machine learning models that support utility clients and internal teams.
Key Responsibilities
- →Team Leadership: Lead and scale a cross-functional team of Machine Learning Engineers and Software Engineers.
- →LLM & AI Solutions: Drive the development of intelligent tools for customer and water/energy specialists (e.g., LLM-based Answer Bots) and end-users (e.g., VoiceBots) that improve service efficiency.
- →Predictive Modeling: Guide the team in delivering predictive ML models for utility clients—such as water leak detection, churn prediction and contact propensity — ensuring robustness, explainability, and client value.
- →Technical Vision: Set the technical vision for AI & analytics products while being hands-on in system design, architecture reviews, and high-impact technical decisions.
- →Innovation: Champion experimentation and fast iteration to explore new use cases with GenAI and classic ML, staying at the forefront of emerging technologies like RAG and agentic workflows.
Requirements
- ✓Leadership: Proven leadership experience managing multi-disciplinary engineering teams (6-8 engineers). An inspirational leadership style with the ability to lead through ambiguity is essential.
- ✓ML Lifecycle: Understanding of the ML lifecycle—from data ingestion and feature engineering to model training, evaluation, and deployment in production.
- ✓LLM Expertise: Hands-on experience deploying LLM-based systems (e.g., RAG pipelines, tool calling, fine-tuning, RLHF) and integrating them into real-world applications.
- ✓Product Focus: Experience developing customer-facing AI tools, voice-based interfaces, or agent augmentation systems is highly desirable.
- ✓Architecture: Strong architectural skills and the ability to make pragmatic decisions between prototypes and production-grade systems.
- ✓Tech Stack: Familiarity with modern AI/ML stacks: Python, Kubernetes, PyTorch, LangChain, vector databases, etc..
