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Key Responsibilities :

- Design, develop, and maintain advanced AI/ML/GenAI applications, ensuring robust performance and scalability.
- Drive the end-to-end pipeline for ML development and deployment, encompassing data collection, data analysis, model training, validation, deployment, and integration.
- Apply expertise in LLMs, including prompt engineering and the utilization of vector databases for efficient information retrieval.
- Leverage containerization technologies such as Docker and Kubernetes, along with cloud platforms like Google Cloud Platform (GCP), for scalable and efficient deployment.
- Lead and guide junior engineers, conduct code reviews, facilitate planning sessions, and provide technical mentorship to foster team growth and excellence.
- Utilize AI and ML techniques to accelerate and optimize software development cycles, enhancing productivity and efficiency.
- Collaborate effectively with cross-functional teams to define, design, and implement recent features and functionalities.
- Write clean, efficient, and well-documented code, adhering to high-quality coding standards and best practices.
- Troubleshoot and debug software issues, ensuring the stability and reliability of deployed applications.
- Conduct research and experimentation to explore new machine learning approaches and technologies.
- Contribute to the continuous improvement of software development processes, methodologies, and best practices.

Educational Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science,



or a related quantitative field.
- Equivalent practical experience will also be considered.

Must-Have Skills :

- Strong logical reasoning and analytical problem-solving skills.
- In-depth understanding of Data Structures and Algorithms (DSA).
- Proficiency in Machine Learning (ML) concepts and algorithms.
- Expertise in Natural Language Processing (NLP) and Large Language Models (LLMs).
- Solid foundation in Deep Learning architectures and frameworks.
- Proven experience in end-to-end ML development, deployment and monitoring pipelines.
- Experience with LLM applications, including prompt engineering and vector databases.
- Experience with DevOps and CI/CD practices for ML pipelines.
- Hands-on experience with containerization technologies (Docker, Kubernetes).
- Experience with cloud platforms (e.g., AWS, Azure, GCP).
- Demonstrated ability to lead and guide technical teams, including code reviews and planning sessions.
- Excellent communication, leadership, and problem-solving skills.

Good-to-Have Skills :

- Experience in backend development and integration using technologies such as FastAPI, .NET.
- Familiarity with NoSQL databases like MongoDB, and search engines like Elasticsearch.
- Experience with message queuing systems like RabbitMQ.
- Experience with SLM fine-tuning and PEFT techniques like LoRA, QLoRA, etc.
- Experience in agentic application development.

Education :

- Bachelors degree in a technical discipline.

Experience Level :

- As a Technical Lead - 4 - 7 years of experience.

📌 Tescra Software - ML Technical Lead (India)
🏢 Texlon
📍 India