Senior Machine Learning Engineer
First seen by Alion on Jul 21, 2026.
About the job:
About Client:
We are pioneering the Autopilot Enterprise. Our conversational AI agents handle workflows, drive outcomes, and deliver measurable impact for businesses. Born from the belief that enterprises need a new playbook, we build autonomous, multilingual agents capable of complex reasoning, contextual understanding, and end-to-end workflow ownership.
Role Overview:
We are seeking an experienced ML Engineers (Senior) to drive the development of next-generation conversational and dynamic AI agents. You will architect and scale systems that enable:
Conversational Agents (Voice & Chat):
- Human-like, open-ended dialogues without rigid workflow design.
- Dynamic reasoning to achieve goals (e.g., selling a personal loan).
- Continuous self-learning from conversation outcomes.
- Operating at minimal latency and cost.
Dynamic Workflow Agents:
- Agents that learn workflows (Sales, Support, Admin) by observing humans.
- Self-learning from live agent behavior, recordings, and transcripts.
- Ability to see, process/understand, reason, and interact with GUIs/browsers.
- One-shot learning from escalations, ensuring accurate human-AI collaboration.
- Human agent assist & copilot features driven by workflow context.
This is a rare opportunity to shape how enterprises adopt agentic AI, working directly at the intersection of AI research, applied ML, scalable infrastructure, and real-world enterprise workflows.
Key Responsibilities:
1. Leadership & Vision:
- Lead and mentor a team of engineers building agentic AI systems.
- Define technical vision, architecture, and product strategy.
2. Architecture & Delivery:
- Design and scale enterprise-grade AI products leveraging reinforcement learning, computer vision, and LLM fine-tuning.
- Drive low-latency, cost-optimized systems in production.
- Ensure robust engineering standards, testing, and security practices.
3. Innovation & Integration:
- Develop pipelines for self-learning agents from conversations and human workflows.
- Architect systems for human-in-the-loop escalation and AI copilots.
- Collaborate with product, design, and research teams to deliver real-world outcomes.
4. Operational Excellence:
- Establish CI/CD pipelines, automation, and best practices.
- Proactively identify risks and resolve technical challenges.
- Optimize for scalability, reliability, and enterprise integration.
What are we looking for:
- Experience: 2-8 years of experience.
- AI/ML Skills: Strong expertise in Reinforcement Learning, Computer Vision, LLM fine-tuning, and applied ML research.
- Systems Expertise: Proven ability to build and scale large-scale distributed systems and enterprise-grade products.
- Infrastructure Skills: Deep understanding of cloud platforms (AWS, GCP, Azure) and scalable architecture.
- Hands-on Engineering: Proficiency in Python, Go, Java, or equivalent languages.
- Mindset: Passion for building product-first AI systems (not services), strong execution ability, and innovation-driven leadership.
Why Join:
- Work at the cutting edge of AI and enterprise technology.
- Be part of a mission-driven, high-growth startup.
- Direct impact on products used by large-scale enterprise clients.
- A vibrant and dynamic work environment fostering professional growth and innovation.
- Competitive compensation and performance-based incentives.
- A front-row seat in the GenAI revolution, working with a team of passionate, like-minded innovators.
Skills
Machine Learning, Data Science, Data Scientist, Conversational AI, Agentic AI, Artificial Intelligence, LLM, AWS, Azure