Senior Software Engineer - AI

Nstarx India; Hyderabad; On-site; INR 3,500,000 - 5,000,000; Full time

Job summary

NStarX in Hyderabad is seeking a Senior Software Engineer AI to design, develop, and deploy GenAI solutions, mentoring a team, and driving enterprise-grade GenAI delivery.

The role emphasizes leading AI/ML projects, collaborating across functions, and delivering scalable GenAI applications across text, code, image, and audio modalities.

Qualifications

• 9+ years of experience in AI/ML engineering or related roles.
• 3+ years of Generative AI with team leadership responsibilities.
• Proven track record of production-grade ML and GenAI model development and deployment.

Responsibilities

• Design, develop, and deploy ML models and AI algorithms for business challenges.
• Lead and mentor a team of AI/ML engineers for scalable solutions.
• Collaborate with data scientists, software engineers, PMs, and UX designers.

Skills

Leadership

Mentoring

Cross-functional collaboration

Problem solving

Education

Bachelor's or Master's in CS/ML

PhD is a plus

Tools

Python

Hugging Face Transformers

Diffusers

LangChain

TGI

FastAPI

gRPC

NVIDIA Triton

TorchServe

AWS SageMaker

GKE / AKS

Kubeflow

MLflow

Job description

Job Description

Position: Senior Software Engineer AI

Location: Hyderabad (Work from Office)

Job Summary

NStarX is seeking a highly skilled Senior Software Engineer AI with a strong focus on Generative AI to join our team in Hyderabad.

This individual will play a key role in designing, developing, and deploying innovative AI solutions, mentoring a team, and contributing to enterprise-grade GenAI product delivery.

Key Responsibilities

• Design, develop, and deploy machine learning models and AI algorithms to address complex business challenges.
• Lead and mentor a team of AI/ML engineers, ensuring quality and scalability in solution design and implementation.
• Collaborate closely with cross-functional teams including data scientists, software engineers, product managers, and UX designers.
• Lead the development and deployment of Generative AI applications across text, code, image, and audio modalities using state-of-the-art LLMs.
• Design and implement CI/CD pipelines for the GenAI model lifecycle including training, validation, packaging, and deployment.
• Apply best practices for model performance tuning, cost optimization, and scalable deployment in cloud and hybrid environments.
• Develop prompt engineering, fine-tuning strategies (LoRA, QLoRA, PEFT), and evaluation protocols tailored to business use cases.
• Stay current with emerging trends in AI, ML, and Generative AI and drive adoption across teams.
• Document processes, model architectures, and deployment strategies for traceability and knowledge sharing.

Project Collaboration

• Work closely with cross-functional teams to gather requirements and deliver high-quality solutions.
• Participate in project discussions, provide technical insights, and share recommendations.

Leadership Guidance

• Provide guidance and mentorship to junior developers.
• Take ownership of deliverables and ensure alignment with organizational standards.

Additional Skills

• Java web application development for integration purposes (preferred but not mandatory).
• Strong cloud computing knowledge for building scalable and efficient solutions.

Education

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field (PhD is a plus).

Experience

• 9+ years of experience in AI/ML engineering or related roles.
• 3+ years of experience in Generative AI with team leadership responsibilities.
• Proven track record of production-grade ML and GenAI model development and deployment.

Technical Expertise

• Programming: Python (preferred).
• GenAI Frameworks: Hugging Face Transformers, Diffusers, LangChain, TGI.
• Serving Inference: FastAPI, gRPC, NVIDIA Triton, TorchServe.
• Cloud Platforms: AWS SageMaker, EKS, Vertex AI, GKE, Azure ML, AKS.
• MLOps DevOps: Kubeflow, MLflow, GitHub Actions, Jenkins, Helm, Terraform.
• Optimization Techniques: Model quantization, distillation, pipeline and tensor parallelism.
• Data Science Evaluation: pandas, NumPy, scikit-learn, Matplotlib, Seaborn, statistical modeling, A/B testing.

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong leadership and mentoring abilities.
• Excellent verbal and written communication skills.
• Ability to bridge technical and non-technical teams.
• Comfortable working in a fast-paced, collaborative environment.