Machine Learning Engineer

AI / Machine Learning Engineer

We're an early-stage startup with established clients and a portfolio of contracts, specializing in the delivery of Agentic AI systems across diverse sectors including transportation, marketing, and academia. We're seeking a highly skilled and experienced AI / Machine Learning Engineer to join our dynamic team.

In this pivotal role, you'll be instrumental in designing, developing, deploying, and optimizing cutting-edge AI agents and multi-agent systems that autonomously execute complex actions. You'll work with a comprehensive range of technologies and data modalities, from leading AI frameworks to robust cloud and on-premise deployment solutions, driving innovation in real-world applications.

Key Responsibilities :

• Agentic AI Development : Design, develop, and implement sophisticated AI agents and bots capable of independent operation, complex decision-making, and self-correction within various domain-specific contexts.

Utilize and seamlessly integrate with advanced AI orchestration frameworks such as LangChain and LangGraph , and potentially the Microsoft Bot Framework , to build robust conversational and task-oriented agents.

Work with state-of-the-art large language model (LLM) serving solutions like Ollama and vLLM to ensure efficient and scalable inference for our AI agents.

Implement Retrieval-Augmented Generation (RAG) systems to enable agents to access, synthesize, and generate responses based on external, up-to-date knowledge bases, mitigating hallucinations and ensuring factual accuracy.

Develop and integrate Memory, Reasoning, and Planning (MRP) capabilities within agents, allowing them to maintain context, reason over information, formulate multi-step plans, and adapt to dynamic environments.

Design and implement Agent-to-Agent (A2A) communication protocols , enabling seamless and secure collaboration, task delegation, and information exchange between different autonomous agents, regardless of their underlying frameworks or platforms.

Work across diverse data modalities including image, time-series, text, and graph data , developing models and agents that can interpret, process, and generate insights from heterogeneous data sources.

Expose AI functionalities through well-documented and performant APIs, enabling seamless integration with client systems and applications.

Handle on-premise deployments, which includes the end-to-end setup, configuration, and maintenance of Kubernetes clusters for containerized applications.

Implement robust containerization strategies (e.g., Docker) and establish efficient orchestration workflows using tools like Argo to automate deployment, scaling, and management of AI services.

Establish and maintain CI / CD pipelines for AI models and applications, ensuring rapid iteration and reliable delivery.

Conduct experimentation, hyperparameter tuning, and model evaluation to achieve optimal model performance.

Stay abreast of the latest research and advancements in AI / ML, particularly in the areas of large language models and agentic AI, to continuously improve our systems.

Essential Skills and Experience :

Bonus Points :