Artificial Intelligence Engineer

Srs Business Solutions India; Hyderabad; Presencial; INR 4.000.000 - 6.000.000; Jornada completa

Descripción de la vacante

Srs Business Solutions India in Hyderabad seeks an experienced AI Lead Engineer to drive design, development, and scaling of AI/ML initiatives, bridging cutting-edge research with production-grade software engineering.

You will lead architectural direction, deploy scalable models, and mentor a team of software and ML engineers, while establishing robust MLOps pipelines and governance.

Formación

• Leadership in AI strategy and architecture.
• Experience deploying ML models to production.
• Strong mentoring and team-building skills.

Responsabilidades

• Drive architectural vision and execution strategy for AI/ML systems.
• Design, train, fine-tune, and deploy scalable ML models and LLM apps into production.
• Lead and upskill a team of software and ML engineers; promote high quality and learning.
• Establish MLOps, CI/CD pipelines for AI, model monitoring, data governance, and code reviews.
• Collaborate with Product Managers, Data Engineers, and stakeholders to translate business problems into AI solutions.
• Monitor and optimize AI models and infrastructure for latency, cost, accuracy, and scalability.

Conocimientos

AI leadership

MLOps

Production ML

Team mentorship

Herramientas

Python

TensorFlow

PyTorch

Descripción del empleo

Role:AI Lead Engineer

Exp: 7+ Years

Location: Hyderabad

We are looking for an ambitious and hands-on AI Lead Engineer to spearhead the design, development, and scaling of our next-generation artificial intelligence and machine learning initiatives. In this role, you will bridge the gap between cutting-edge AI research and production-grade software engineering.

Key Responsibilities

• Technical Leadership & Strategy: Drive the architectural vision, technical direction, and execution strategy for AI and machine learning systems.
• Model Development & Productionization: Design, train, fine-tune, and deploy scalable machine learning models, deep learning architectures, and Large Language Model (LLM) applications (RAG, agents, prompt orchestration) into production.
• Team Mentorship & Growth: Lead, mentor, and upskill a team of talented software and ML engineers, fostering a culture of high quality, innovation, and continuous learning.
• Code & Architecture Reviews: Establish best practices for MLOps, CI/CD pipelines for AI, model monitoring, data governance, and rigorous code reviews.
• Cross-Functional Collaboration: Partner with Product Managers, Data Engineers, and Stakeholders to translate complex business problems into viable, high-impact AI solutions.
• Performance & Optimization: Continuously monitor and optimize AI models and infrastructure for latency, cost-efficiency, accuracy, and scalability.