Explore AI/ML Engineer jobs in Bangalore for professionals with hands-on experience in artificial intelligence, machine learning, deep learning, and production-grade AI systems. These opportunities focus on designing, developing, deploying, and optimizing intelligent applications using Python, ML frameworks, cloud platforms, and modern Generative AI technologies.
Job Overview
Job Role: AI/ML Engineer
Location: Bangalore / Bengaluru, Karnataka
Experience: Entry-Level to Experienced Professionals
Employment Type: Full-Time
Job Category: Artificial Intelligence / Machine Learning
Salary: Open for the right candidates
Qualification: B.E / B.Tech / M.Tech / MCA / M.Sc / Computer Science / AI / Data Science or equivalent
Work Mode: On-site / Hybrid depending on employer requirements
Key Responsibilities
- Design, develop, and maintain machine learning and AI-based applications.
- Build, train, evaluate, and optimize machine learning models.
- Develop scalable ML pipelines for training and inference.
- Implement classification, regression, recommendation, forecasting, and anomaly-detection solutions.
- Work with structured and unstructured datasets for AI applications.
- Perform data preprocessing, feature engineering, and model optimization.
- Develop deep learning models using appropriate frameworks.
- Integrate trained models with applications through APIs and backend services.
- Build and optimize AI inference services for production environments.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, DevOps teams, and product stakeholders.
- Monitor model performance and address accuracy, latency, scalability, and reliability issues.
- Maintain technical documentation for AI models, pipelines, APIs, and deployment processes.
Required AI/ML Skills
Candidates should have strong programming skills in Python and practical knowledge of machine learning concepts.
Relevant technical skills may include:
Machine Learning: Scikit-learn, supervised learning, unsupervised learning, classification, regression, clustering, ensemble methods and model evaluation.
Deep Learning: TensorFlow, PyTorch, Keras, neural networks, CNNs, RNNs, Transformers or related architectures.
Programming: Python, SQL, object-oriented programming, data structures, algorithms and API development.
Data Processing: Pandas, NumPy, data preprocessing, feature engineering and dataset preparation.
Model Development: Model training, hyperparameter tuning, cross-validation, performance evaluation and optimization.
Generative AI & LLM Skills
For Generative AI-focused openings, experience with Large Language Models (LLMs), Natural Language Processing, Transformers, prompt engineering, embeddings, vector databases and Retrieval-Augmented Generation (RAG) can be valuable.
Candidates may also work on applications such as AI assistants, intelligent search, document processing, text classification, summarization, recommendation engines, conversational AI, and enterprise knowledge systems.
Knowledge of frameworks and tools used for developing LLM-powered applications can be an added advantage.
MLOps & Model Deployment
AI/ML Engineers may be expected to move models beyond experimentation and into production environments.
Relevant skills can include Docker, Kubernetes, MLflow, Airflow, Git, CI/CD pipelines, model serving, API deployment, monitoring, version control and automated ML workflows.
Experience deploying AI/ML workloads on AWS, Microsoft Azure or Google Cloud Platform (GCP) is valuable for cloud-based projects.
Entry-Level AI/ML Engineer Roles
Candidates starting their AI/ML careers should have strong fundamentals in Python, machine learning, statistics, algorithms and data handling.
Academic projects, internships, certifications, GitHub projects, hackathons, or practical AI applications can help demonstrate technical ability.
Candidates should be prepared to explain how they prepared data, selected algorithms, trained models, evaluated results, and solved problems during their projects.
Mid-Level AI/ML Engineer Roles
Mid-level professionals should have hands-on experience developing machine learning applications and integrating models into software systems.
They may be responsible for ML pipelines, API development, model optimization, cloud deployment, inference services, data processing, and production monitoring.
Experience working with real-world datasets and production applications is highly desirable.
Senior AI/ML Engineer Roles
Senior professionals may take responsibility for designing scalable AI architectures, selecting appropriate models and frameworks, improving inference performance, and defining engineering standards.
Depending on the position, senior engineers may also mentor developers, review AI/ML solutions, design MLOps workflows, evaluate new AI technologies, and work closely with engineering and product leadership.
Common AI/ML Job Profiles
Relevant openings may include AI Engineer, Machine Learning Engineer, Generative AI Engineer, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, LLM Engineer, Applied AI Engineer, MLOps Engineer and AI Software Engineer.
Each role can have different technical requirements, so candidates should apply to positions matching their primary AI/ML expertise.
Preferred Technical Exposure
Experience with some of the following technologies can strengthen a candidate’s profile:
Python, TensorFlow, PyTorch, Scikit-learn, SQL, Spark, PySpark, Docker, Kubernetes, MLflow, AWS, Azure, GCP, REST APIs, NLP, Transformers, LLMs, RAG, vector databases and Git.
Knowledge of software engineering practices, system design, data structures, algorithms, cloud computing, and application security can also be useful for production-focused AI roles.
Candidate Requirements
Candidates should demonstrate strong analytical and problem-solving abilities along with practical AI/ML engineering knowledge.
Good communication and collaboration skills are important because AI/ML Engineers frequently work across data, engineering, infrastructure, and business teams.
Experienced applicants should highlight production AI/ML projects, models developed, frameworks used, cloud exposure, deployment experience, measurable outcomes, and technical responsibilities in their resumes.
Apply for AI/ML Engineer Jobs in Bangalore
Candidates searching for AI/ML Engineer jobs in Bangalore can apply with an updated resume highlighting relevant Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, and MLOps experience.
The recruitment process may include Python coding, machine learning fundamentals, ML system design, model-development discussions, project evaluation, Generative AI concepts, technical interviews, and HR discussions.
Salary is open for the right candidates and may vary according to relevant experience, AI/ML expertise, technical skills, interview performance, and employer requirements.