Job Description
Designation: ML & Generative AI Engineer (Senior)
Location: Gurugram (WFO)
Experience: 6+ Years
Industry: AI Product (B2 B Solution)
Overview
We are a fast-growing, technology-driven organization focused on building intelligent, scalable AI solutions that create measurable business impact. Our teams work on cutting-edge machine learning and Generative AI use cases, transforming complex data into production-grade systems used across products and platforms.
This role offers an opportunity to work closely with cross-functional stakeholders, take ownership of AI-driven initiatives, and contribute to the evolution of modern ML and Gen AI systems in a real-world production environment.
Key Responsibilities
- Design, build, and deploy end-to-end machine learning and Generative AI pipelines for production use
- Develop and optimize ML models, deep learning systems, and LLM-based solutions
- Implement Generative AI use cases including RAG pipelines, prompt engineering, fine-tuning, and agent-based workflows
- Collaborate with data scientists, backend engineers, and product teams to integrate AI capabilities into existing systems
- Apply MLOps best practices such as model versioning, experiment tracking, CI/CD, and performance monitoring
- Participate in technical design discussions and contribute to AI architecture decisions
- Analyze large datasets to improve model accuracy, efficiency, and scalability
- Stay current with emerging AI/ML tools, frameworks, and methodologies and apply them where relevant
- Clearly communicate technical outcomes, trade-offs, and recommendations to stakeholders.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field
- 6+ years of experience in software engineering, with strong focus on AI/ML development
- Strong proficiency in Python and hands-on experience with ML frameworks such as Py Torch, Tensor Flow, scikit-learn
- Practical experience working with Large Language Models (LLMs) including proprietary or open-source models
- Experience building Generative AI solutions such as RAG systems, prompt engineering, or fine-tuning workflows
- Exposure to cloud platforms (AWS, GCP, or Azure) for ML model training and deployment
- Understanding of MLOps practices including model deployment, monitoring, and experimentation
- Strong problem-solving skills and ability to work collaboratively in cross-functional teams
Location: Gurugram (WFO)
Experience: 6+ Years
Industry: AI Product (B2 B Solution)
Overview
We are a fast-growing, technology-driven organization focused on building intelligent, scalable AI solutions that create measurable business impact. Our teams work on cutting-edge machine learning and Generative AI use cases, transforming complex data into production-grade systems used across products and platforms.
This role offers an opportunity to work closely with cross-functional stakeholders, take ownership of AI-driven initiatives, and contribute to the evolution of modern ML and Gen AI systems in a real-world production environment.
Key Responsibilities
- Design, build, and deploy end-to-end machine learning and Generative AI pipelines for production use
- Develop and optimize ML models, deep learning systems, and LLM-based solutions
- Implement Generative AI use cases including RAG pipelines, prompt engineering, fine-tuning, and agent-based workflows
- Collaborate with data scientists, backend engineers, and product teams to integrate AI capabilities into existing systems
- Apply MLOps best practices such as model versioning, experiment tracking, CI/CD, and performance monitoring
- Participate in technical design discussions and contribute to AI architecture decisions
- Analyze large datasets to improve model accuracy, efficiency, and scalability
- Stay current with emerging AI/ML tools, frameworks, and methodologies and apply them where relevant
- Clearly communicate technical outcomes, trade-offs, and recommendations to stakeholders.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field
- 6+ years of experience in software engineering, with strong focus on AI/ML development
- Strong proficiency in Python and hands-on experience with ML frameworks such as Py Torch, Tensor Flow, scikit-learn
- Practical experience working with Large Language Models (LLMs) including proprietary or open-source models
- Experience building Generative AI solutions such as RAG systems, prompt engineering, or fine-tuning workflows
- Exposure to cloud platforms (AWS, GCP, or Azure) for ML model training and deployment
- Understanding of MLOps practices including model deployment, monitoring, and experimentation
- Strong problem-solving skills and ability to work collaboratively in cross-functional teams
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