Cloud Technologies – Senior Machine Learning Engineer

Job Description

Responsibilities :

– Develop Deep Learning models, focusing on NLP, Large Language Models (LLMs), and Generative AI.

– Design and implement agentic workflows and multi-agent systems for autonomous task execution and decision-making.

– Build intelligent agents capable of planning, reasoning, and executing complex workflows with minimal human intervention.

– Deep understanding of architectures, hyperparameters, and training techniques to achieve state-of-the-art results.

– Prepare and preprocess datasets, including managing vector stores for efficient data retrieval.

– Train and fine-tune models, implementing RAGs (Retrieval-Augmented Generation) to enhance content relevance and accuracy.

– Develop agent orchestration systems that can coordinate multiple AI models and tools to accomplish complex business objectives.

– Deploy scalable, robust models to production environments.

– Translate business requirements into technical solutions by working with cross-functional teams.

– Continuously research and adopt advancements in Deep Learning, NLP, and LLMs.

– Maintain comprehensive documentation of models, code, and workflows.

– Participate in code reviews and provide constructive feedback to ensure code quality.

– Research and implement advanced ML techniques to improve model accuracy and efficiency.

– Communicate technical concepts and project updates effectively to both technical and non-technical stakeholders.

Desired Skills & Expertise :

– Expertise in NLP techniques (e.g., text classification, sentiment analysis, text generation).

– Strong understanding of large language models and their applications.

– Experience with agentic AI frameworks and multi-agent systems (e.g., LangGraph, LangChain, AutoGen, CrewAI, or similar).

– Knowledge of agent planning algorithms, tool integration, MCP and autonomous decision-making systems.

– Experience with workflow orchestration tools and agent deployment frameworks.

– Deep Understanding of prompt engineering, function calling, and tool use in LLM-based agents.

– Experience in Monitoring agent drift, hallucinations, failure modes

– Design and implement guardrails to ensure model safety, reduce hallucinations, and prevent prompt-based vulnerabilities.

– Build robust logging, tracing, and analytics systems to monitor agent behavior, performance, and workflow execution.

– Proficiency in Python and experience with data engineering/pipeline development.

– Hands on experience in cloud platforms like AWS, GCP, or Azure, and knowledge of MLOps.

– Exposure to containerization tools like Docker or orchestration tools like Kubernetes.

Good to Have :

– Experience with web development frameworks such as Flask, Django, or Fast API.

– Knowledge of reinforcement learning and its applications in agent training.

– Experience with graph databases and knowledge representation for agent reasoning.

– Familiarity with distributed systems and microservices architecture for agent deployments.

– Understanding of human-AI interaction patterns and agent user experience design.

Education :

– Bachelor’s degree in computer engineering (BE) or equivalent.

Requirements :

– 4 – 5 years of relevant industry experience

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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