InvoLead
Website:
involead.com
Job details:
Company Description
InvoLead is a data science consulting firm specializing in advanced analytics, machine learning, and applied intelligence to address complex business challenges. InvoLead partners with clients to transform them into data-driven organizations, enabling informed decision-making over intuition-based approaches. With expertise in marketing analytics, customer analytics, sales forecasting, machine learning, and cloud-based implementations (Azure, AWS, GCP), InvoLead delivers end-to-end scalable solutions. The company emphasizes collaboration, transparency, and continuous innovation, ensuring tailored solutions and sustainable business impact.
Position: ML Engineer/Generative AI Engineer
Experience: 3+ years Job
Location: Gurgaon
Employment Type: Full-time
Notice Period : Immediate - 30 days
Role Description
This is a full-time, on-site role based in Gurugram for a Generative AI Engineer.
We are seeking a highly skilled ML / Generative AI Engineer with strong hands-on experience in designing, building, orchestrating, and deploying production-grade Generative AI solutions.
The ideal candidate should possess a strong academic foundation in Machine Learning / Artificial Intelligence, advanced proficiency in Core Python, and practical expertise in Agentic AI systems and multi-agent orchestration frameworks, including LangGraph-based workflows.
In this role, you will work on solving real-world business challenges by architecting and deploying scalable multi-agent Generative AI systems capable of concurrent task execution and intelligent decision-making.
Key responsibilities
• Design, develop, and implement state-of-the-art generative models for various applications, such as text generation, image synthesis and content creation. • Implement Agentic AI architectures using frameworks such as LangGraph, LangChain, and custom orchestration logic. • Experience working on open source LLMs like Llama, Falcon, BERT, Mistral etc., RAG systems and prompt engineering • Pre-process and analyze large datasets to extract meaningful features and patterns suitable for training generative models. • Optimize and fine-tune generative models for efficiency, scalability, and improved performance. • Deploy and manage AI solutions on cloud platforms (AWS / Azure), following best practices. • Implement strategies for reducing model latency and resource consumption. • Develop and implement robust evaluation metrics to assess the performance and quality of generative models. • Architecture design and building scalable production systems • Document code, models, and methodologies thoroughly to facilitate knowledge sharing and future development. • Stay updated with the latest advancements in generative models, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other relevant techniques. • Stay at the forefront of the latest research papers and publications in the field of generative AI. • Contribute to the company's intellectual property by researching and developing novel approaches to address specific business challenges. • Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate generative models into real world applications. • Provide technical expertise and guidance to team members on generative AI related projects.
Qualifications
• B Tech/M Tech in Computer/IT or related field from reputed engineering colleges • 3 - 6 years of hands-on experience in ML domain. • Practical experience with Generative AI & LLMs, Agentic AI and multi-agent systems, LangGraph, LangChain, Hugging Face, OpenAI APIs, RAG architecture and vector databases. • Proven experience in developing generative models, with expertise in deep learning frameworks such as TensorFlow or PyTorch. • Strong programming skills in languages like Python and proficiency in machine learning libraries. • Solid understanding of neural network architectures, optimization techniques, and training methodologies • Work experience on cloud platforms like AWS/Azure is desired.
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