Job Description: Senior AI/ML Engineer (15+ Years Experience)Job Title: Senior AI/ML Engineer / Lead AI Architect
Experience: 15+ years
Location: Bangalore
Employment Type: Full-time
Role OverviewWe are seeking a highly skilled Senior AI/ML Engineer with deep expertise in designing, developing, and deploying scalable AI, machine learning, and deep learning solutions. The ideal candidate has strong experience in modern AI frameworks, cloud platforms, MLOps, and building secure, production-grade AI systems. This role requires both technical leadership and handson capability to architect high-impact AI solutions across the enterprise.
Key Responsibilities1. AI/ML Solution Architecture- Design and architect endtoend AI/ML platforms, pipelines, and production systems.
- Lead development of advanced ML models, deep learning architectures, and GenAI/LLM-based solutions.
- Define scalable data processing and model deployment strategies using cloud-native services (Azure/AWS/GCP).
- Evaluate emerging AI technologies, tools, and frameworks for enterprise adoption.
2. Model Development & Optimization- Build and optimize supervised, unsupervised, and reinforcement learning models.
- Develop deep learning models using frameworks like TensorFlow, PyTorch, Keras.
- Fine-tune LLMs, implement prompt engineering best practices, and apply RAG-based architectures.
- Conduct feature engineering, model tuning, hyperparameter optimization, and performance benchmarking.
3. MLOps & Deployment- Implement and maintain CI/CD pipelines for model development and deployment.
- Build robust monitoring (drift detection, bias detection, performance metrics).
- Automate ML lifecycle using tools such as Azure ML, SageMaker, MLflow, Kubeflow, Databricks.
- Ensure scalable and reliable deployment using containers, Kubernetes, and microservices.
4. Data Engineering & Integration- Collaborate with data engineering teams to design pipelines for ingestion, transformation, and storage.
- Work with large-scale structured and unstructured datasets including text, audio, video, and sensor data.
- Implement data quality, preprocessing, and governance best practices.
5. Thought Leadership & Mentoring- Provide technical leadership and guidance to junior engineers and cross-functional teams.
- Lead technical reviews, architecture discussions, and innovation initiatives.
- Collaborate with product, engineering, and business teams to identify AI opportunities and create roadmaps.
6. Cloud Experience
- Experience with cloud services and architecting the cloud solution
- Experience with architecting solution involving data engineering and complex data science projects
- Hands on experience on Data pipelines, MLOPS, AIOPS and CloudOPS projects
- Hands on experience in any of the core technology aspect, programming languages like Python etc.
7. Domain experience specially in medical, automobile industries would be added plus
Required Skills & Qualifications- 15+ years of experience in AI/ML engineering, advanced analytics, or data science.
- Strong proficiency in Python, including libraries such as NumPy, Pandas, SciPy, and scikitlearn.
- Advanced experience with TensorFlow, PyTorch, Keras, and modern LLM frameworks.
- Strong background in computer science, mathematics, statistics, and algorithm design.
- Experience with cloud platformsAzure, AWS, or GCPfor AI workloads.
- Hands-on expertise in MLOps, CI/CD, Docker, Kubernetes, and ML lifecycle management.
- Experience working with large-scale datasets, distributed processing (Spark, Ray), and data lakes.
- Solid understanding of responsible AI principles, fairness, bias mitigation, and model interpretability.
- Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field (PhD preferred).
Preferred Skills- Experience with Generative AI, LLMs, prompt engineering, and vector databases (FAISS, Pinecone, Weaviate).
- Familiarity with real-time inference systems and edge AI.
- Experience in domain-specific AI such as NLP, computer vision, forecasting, or recommendation systems.
- Certifications in cloud or AI (Azure AI Engineer, AWS ML Specialty, Google ML Engineer).
Soft Skills- Excellent communication and cross-functional collaboration abilities.
- Strong analytical thinking and problem-solving mindset.
- Ability to lead complex projects with minimal supervision.
- Innovation-driven mindset with passion for continuous learning.
