Job Summary

We are seeking a highly experienced Senior Lead Engineer with 5 to 10 years of expertise in advanced AI technologies, automation frameworks, and cloud-native solutions. The ideal candidate will be a hands-on technologist with robust leadership skills, capable of designing, implementing, and mentoring teams on cutting-edge AI-driven workflows and microservice architectures.

Responsibilities

- ML Model Development : Design and implement scalable machine learning models tailored to business needs.
- Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise-grade knowledge systems.
- Model Training & Evaluation : Build robust training pipelines, optimize hyperparameters, and evaluate models using industry-standard metrics.
- Build scalable applications using Python and integrate with Microservices.
- Feature Engineering : Develop and maintain efficient feature extraction and transformation processes to improve model accuracy and performance.
- Ensure seamless cloud-based AI deployments across AWS, Azure, or GCP.
- MLOps : Implement CI/CD pipelines for ML workflows, ensuring reproducibility, scalability, and automation of model lifecycle management.
- Collaborate with cross-functional teams to embed AI into existing enterprise systems.
- Model Deployment : Lead deployment of ML models into production environments, ensuring reliability, monitoring, and continuous improvement.
- Foster a culture of innovation, knowledge-sharing, and continuous improvement.
- Collaboration & Leadership :



Partner with cross-functional teams (Data Science, Product, Engineering) to deliver impactful solutions.
- Mentor and guide junior engineers in best practices.
- Innovation & Research : Stay updated with the latest ML frameworks, tools, and research to continuously enhance organizational capabilities.

Required Skills & Expertise

- 5-10 years in ML engineering, with proven track record of production-grade ML solutions.
- Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
- Solid understanding of cloud platforms (AWS, Azure, GCP) for ML deployment.
- ML Model Development, Training, Evaluation
- Feature Engineering & Data Preprocessing
- Model Deployment & Monitoring
- CI/CD for ML pipelines
- Excellent problem-solving, communication, and leadership abilities.

Qualifications

- Bachelors or Master's degree in Computer Science, Engineering, or related field.
- 5 to 10 years of professional experience in AI, automation, and cloud technologies.
- Track record of delivering enterprise-scale AI solutions.
- Experience in leading technical teams and mentoring junior engineers.

Preferred Qualifications

- Certifications in GCP (e.g., Professional Machine Learning Engineer, Data Engineer).
- Experience in Agile/Scrum methodologies.
- Exposure to MLOps and CI/CD pipelines for ML models.
- Experience working in a product-led company.

📌 Senior ML Engineer (Sikandrabad)
🏢 Tekskills
📍 Sikandrabad