1432 Machine Learning jobs in Bangalore

Company Description

HCL Software is a division of HCL Technologies (HCL) that operates its primary software

business. It develops, markets, sells, and supports over 20 product families in the areas of

DevOps, Security, Automation, Digital Solutions, Data Management, Marketing and Commerce,

and Mainframes. Its mission is to drive ultimate customer success with their IT investments

through relentless innovation of its products.

Job Title: Senior Machine learning engineer /Lead Machine Learning Engineer

Location: India (Bangalore)

Experience required-

• 4 to 7 years
• 10 to 13 years

Responsibilities:

About the Role

We are seeking a highly skilled and experienced Lead Machine Learning Engineer to join our dynamic team supporting a fast-growing e-commerce platform. In this role, you will lead the development and deployment of intelligent systems that enhance user experience, optimize operations, and drive business growth. You will work closely with cross-functional teams to build scalable ML solutions, leveraging modern agentic frameworks and cloud-native technologies.

We are seeking an experienced and innovative Lead Machine Learning Engineer to join our team supporting a fast-growing e-commerce platform. In this role, you will lead the design, development, and deployment of machine learning solutions that drive business value. You will collaborate with fellow engineers, cloud architects, and product teams to deliver scalable ML systems in production, mentor team members, and help define best practices for the organization.

Key Responsibilities

• Lead the end-to-end development and deployment of AI applications, from data exploration and feature engineering to model training, evaluation, and productionization.
• Architect and implement scalable ML pipelines and infrastructure in cloud and on-prem environments.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Break down complex implementations into executable tasks for junior engineers, enabling timely implementation of new platform features.
• Guide and mentor a team of ML engineers, fostering a culture of technical excellence and continuous learning.
• Ensure best practices in code quality, testing, version control, and model monitoring.
• Evaluate and recommend new tools, frameworks, and technologies to improve ML workflows.
• Communicate technical concepts and project status to stakeholders at all levels.
• Stay current with the latest research and advancements in machine learning and AI.

Required Qualifications

• experience in AI/ML model development and deployment using Python.
• Proven experience designing, deploying, and maintaining several AI applications in a production environment.
• Proven experience delegating & overseeing task work supporting complex AI implementations.
• Proficiency with cloud platforms (AWS, Azure, GCP) and ML services (e.g., SageMaker, Vertex AI, Azure ML).
• Experience deploying production Agentic and/or Gen AI applications on a cloud platform.
• Experience with data engineering, ETL pipelines, and big data tools (e.g., Spark, Hadoop).
• Familiarity with MLOps practices, CI/CD, and model monitoring.
• Excellent leadership, communication, and collaboration skills.

Preferred Qualifications

• Experience with Azure cloud services (e.g., Azure Blob Storage, Cosmos DB)
• Experience with Databricks, Spark, Spark Streaming
• Experience working with ecommerce data
• Experience with traditional Python ML frameworks (e.g. Tensorflow, XGBoost, Scikit, etc.)
• Experience with Orchestration frameworks (e.g. Dagster)
• Experience writing & maintaining cloud deployment pipelines

About the Role:

We are seeking a talented and motivated Senior Machine Learning Scientist to join our team, contributing to the development of advanced ML solutions for analyzing complex biological datasets. This role offers an exciting opportunity to work at the intersection of machine learning and life sciences, enabling transformative insights from multi-omics and biomedical data.

Key Responsibilities:

• Design, implement, and optimize machine learning algorithms for analyzing biological data, including genomics, transcriptomics, mass spec, and imaging datasets.
• Develop approaches to integrate diverse data types (e.g., multi-omics, clinical, imaging) to derive meaningful biological insights.
• Stay updated with state-of-the-art ML methods and their applications in life sciences to propose innovative solutions.
• Work closely with bioinformaticians, data scientists, and domain experts to ensure seamless integration of ML models into workflows.
• Optimize and deploy ML models on cloud platforms for scalable analysis.
• Collaborate on preprocessing, feature engineering, and quality control of large, noisy biological datasets.

Qualifications :

• Master’s or Bachelor’s & 3-4 years experience in Machine Learning, Computer Science, Bioinformatics, Computational Biology, or a related field.
• Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, deep learning) and statistical methods.
• Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong problem-solving skills with an aptitude for interpreting complex biological data.
• Excellent communication and interpersonal skills, with the ability to work effectively in a collaborative environment.
• Experience working with cloud technologies (like AWS, GCP, Azure) and scalable computing platform

Good-to-have:

• Experience with biological datasets (e.g., NGS, proteomics, or imaging) and applying ML to multi-omics data integration.
• Experience working with cloud technologies and scalable computing platforms
• Familiarity with biomedical ontologies, pathway analysis, or systems biology approaches.
• Strong publication record in ML or bioinformatics journals.

About Eximietas:

Eximietas Design is a leading technology consulting and solutions development firm specializing in Chip design, Firmware & Embedded Software development, Cloud Computing, cybersecurity, and AI/ML domains. Our success is anchored in the unparalleled expertise of our engineering leadership team, who have collectively taped-out over 100+ chips and released countless software solutions for renowned tech giants like Google, Cisco, Microsoft, Oracle, Uber, Broadcom, and Sun. With a commitment to innovation and excellence, we deliver cutting-edge solutions that empower businesses to thrive in the ever-evolving digital landscape. We are an ISO 9001 and ISO 27001 certified company with development centers in the US and India.

Website link:

Please drop your updated resume at

Experience - 4-5years of (Relevant)

Location: Bangalore ( WFO - 5 days )

Job Type: Full-time

We are looking for candidates who have experience in MLOps and DevOps.

Skill Area-

Python

Software Testing (pytest)

Docker

RunAI / Kubernetes

Git & CI/CD (GitHub Actions)

GCP (Cloud Batch, GCR, etc.)

Model Conversion (ONNX, etc.)

Experiment Tracking (W&B, MLflow)

Hydra / Config Management

Hands-on experience in -

Cloud technologies

CI/CD and testing

MLOps tools and practices

Model tracking and versioning

Kubernetes and container orchestration

Interview Process -

1st Interview - Virtual

2nd interview - Virtual

3rd Client interview - F2F at client location in Bangalore (Must)

Headquartered in Finland, Tecnotree Corporation is a leading provider of full-stack Digital BSS for CSPs and DSPs. Founded in 1978, Tecnotree helps customers to monetize and transform their business towards a marketplace of digital services. Together with its customers, Tecnotree empowers people to self-serve, engage, and take control of their own digital life. Tecnotree is listed on Nasdaq Helsinki (TEM1V).

This is a full-time hybrid role for a Machine Learning Engineer, located in Bengaluru with some work from home flexibility. The Machine Learning Engineer will be responsible for designing and implementing scalable machine learning models, developing pattern recognition solutions, creating neural networks, and applying statistical methods. Day-to-day tasks also include algorithm development, data analysis, and collaboration with cross-functional teams.

• Expertise in Pattern Recognition and Neural Networks
• Strong background in Computer Science and Statistics
• Proficiency in developing Algorithms
• Excellent problem-solving and analytical skills
• Ability to work independently and as part of a team
• Experience with machine learning frameworks and tools
• Bachelor's or Master's degree in Computer Science, Data Science, or a related field
• Experience in the telecom or digital services industry is a plus

Role Description

We are seeking a highly skilled Machine Learning Engineer to contribute to diverse healthcare and in-house data initiatives—ranging from complex data analysis and strategic insights to predictive modeling and real-time implementations. You will work closely with cross-functional teams to deliver high-quality, data-driven solutions that drive business impact.

Key Responsibilities

• Develop, implement, and optimize machine learning models for healthcare and internal projects.
• Conduct feature engineering to improve model performance.
• Deliver real-time model predictions and ensure their smooth integration into production systems.
• Collaborate with data scientists, analysts, and product teams to understand requirements and translate them into technical solutions.
• Apply statistical techniques and data analysis to derive insights and recommendations.
• Work with Large Language Models (LLMs) , deep learning architectures, and vector databases where applicable.
• Ensure scalability, efficiency, and reliability of deployed models.

Requirements :

• 1–3 years total professional experience in data or software engineering roles.
• 6–12 months hands-on experience in AI/ML model development and deployment.
• Strong proficiency in Python (mandatory).
• Solid understanding of statistics and its application in data modeling.
• Knowledge of LLMs , deep learning models, and vector databases .
• Experience with feature engineering and implementing real-time predictions.

• Have hands on experience on real time ML Models / Projects
• Coding in Python Language, Machine Learning, Basic SQL, Git, MS Excel
• Experience in using IDE like Jupyter Notebook, Spyder, PyCharm
• Hands on with AWS Services like S3 bucket, EC2, Sagemaker, Step Functions.
• Engage with clients/consultants to understand requirements
• Taking ownership of delivering ML models with high precision outcomes.
• Accountable for high quality and timely completion of specified work deliverables
• Write codes that are well detailed structured and compute efficient

Role Description

We are seeking a highly skilled Machine Leaning Engineer to support various healthcare & in-house data projects, from complex analysis and strategic insights to predictions and modeling. The ideal candidate will have a comprehensive understanding of Python, Statistical Techniques, LLMs, Deep Learning Models, and Vector databases, with the ability to collaborate across teams and provide exceptional solutions. The person should have experience in implementing feature engineering, and real time model predictions.

Responsibilities :

• Build, Refine, and Use ML Engineering platforms and components
• Deploy and operationalize ML models and deep Learning Models (with a focus on LLMs)
• Scaling machine learning algorithms to work on massive data sets and strict SLAs.
• Build and orchestrate model pipelines including feature engineering, inferencing, and continuous model training.
• Collaborate with clients and contribute to technical requirement gathering.
• Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews.
• Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues and dependencies.
• Coaching and Mentoring of young engineers.

Requirements :

• A master’s or bachelor’s degree in Engineering, Computer Science or related field. Additional knowledge of advanced Statistical techniques be a plus
• A minimum of 3-5 years of experience in advanced software engineering with at least 3+ years of hands-on experience in ML development.
• Good fundamentals of Machine Learning and Data Science. Algorithm knowledge, Model Tuning, EDA, overfitting/underfitting, cross-validation, Data wrangling, feature engineering, storytelling with data etc
• Understanding of Statistics principles of Hypothesis testing, distributions, p-values, confidence intervals, Bayesian vs frequentist.
• Good understanding of Python libraries like NumPy, pandas, scikit-learn, matplotlib, seaborn, and performance optimization.
• RAG: Knowledge of retrievers (BM25, DPR), generators (LLMs), and integration methods

Salary upto 20 lpa

Job Title: Machine Learning Engineer (Founding Engineer)

Location: Bangalore, INDIA

Experience Level: Mid to Senior (3–5 years)

About Nexie

At Nexie, we’re revolutionizing the marketing landscape with our innovative agentic AI platform. Our technology empowers businesses to transform their marketing operations through intelligent automation — from ideation to execution and optimization — with a special focus on the ecommerce sector.

We believe in building elegant, AI-first solutions that solve complex problems with simplicity and style. Our mission is to create tools that not only work intelligently but delight users through thoughtful design.

Join Our Founding Team

• Work directly with our successful serial entrepreneur founders (Ashok & Pradeep) who have built and exited startups
• Shape the future of AI-powered marketing technology from the ground up
• See your innovations directly impact hundreds of global customers
• Enjoy significant equity and growth potential as an early team member

Your Impact & Opportunities

• Pioneer our AI systems across multiple domains — predictive analytics, generative content, decision engines, and more
• Design and implement cutting-edge ML infrastructure including experimentation frameworks, embedding systems, and feedback loops
• Collaborate across functions to rapidly prototype, test, and deploy AI solutions that drive measurable business outcomes
• Explore emerging AI technologies and help define the future capabilities of our platform

Ideal Background

• 3~5 years of hands-on experience with machine learning and AI technologies
• Strong programming skills, particularly in Python and modern ML frameworks
• Experience with large language models and generative AI applications
• Background in building data-driven models and systems
• Passion for experimentation, measurement, and continuous improvement

Bonus Skills

• Experience with AI agent systems or multi-step reasoning frameworks
• Knowledge of marketing technology, ecommerce, or customer engagement domains
• Track record of building production ML systems with proper monitoring and evaluation
• Interest in product design and user experience for AI applications

We Value

• Creative problem solvers who thrive in fast-paced environments
• Self-starters comfortable with ambiguity and wearing multiple hats
• Continuous learners who stay at the forefront of AI advancements
• Collaborators who communicate complex ideas with clarity and purpose

If you’re excited about defining the future of AI-powered marketing technology and want to join a team that values innovation, impact, and growth, we’d love to hear from you!

Location- Bengaluru, Mumbai, Pune & Gurugram

Experience - 5-7 yrs

Mode of Work- Hybrid (Remote not possible)

Whom Are we look for : We are looking for a ML Engineers with expertise in Python, Azure Cloud, NLP, and large-scale data processing. The role involves enhancing existing ML models, optimizing embeddings, LDA models, RAG architectures, and migrating data pipelines to Azure Databricks for scalability and efficiency.

Key Responsibilities:

Model Development:

• Model Development & Optimisation
• Train and optimise models for new data providers, ensuring seamless

integration.

• Enhance models for dynamic input handling.
• Improve LDA model performance to handle a higher number of clusters

efficiently.

• Optimise RAG (Retrieval-Augmented Generation) architecture to enhance

recommendation accuracy for large datasets.

• Upgrade Retrieval QA architecture for improved chatbot performance on large

datasets.

Forecasting & Time Series Modelling

• Develop and optimise forecasting models for marketing, demand prediction, and

trend analysis.

• Implement time series models (e.g., ARIMA, Prophet, LSTMs) to improve

business decision-making.

• Integrate NLP-based forecasting, leveraging customer sentiment and external

data sources (e.g., news, social media).

Data Pipeline & Cloud Migration

Migrate the existing pipeline from Azure Synapse to Azure Databricks and retrain

models accordingly - Note: this is required only for the AUB role(s)

• Address space and time complexity issues in embedding storage and retrieval on

Azure Blob Storage.

• Optimise embedding storage and retrieval in Azure Blob Storage for better

efficiency.

MLOps & Deployment

• Implement MLOps best practices for model deployment on Azure ML, Azure

Kubernetes Service (AKS), and Azure Functions.

• Automate model training, inference pipelines, and API deployments using Azure

services.)

Job Description

• Experience in Data Science, Machine Learning, Deep Learning and Gen AI.
• Design, Architect and Execute end to end Data Science pipelines which includes

Data extraction, data preprocessing, Feature engineering, Model building, tuning

and Deployment.

• Experience in leading a team and responsible for project delivery.
• Experience in Building end to end machine learning pipelines with expertise in

developing CI/CD pipelines using Azure Synapse pipelines, Databricks, Google

Vertex AI and AWS.

• Experience in developing advanced natural language processing (NLP) systems,

specializing in building RAG (Retrieval-Augmented Generation) models using

Langchain. Deploy RAG models to production.

• Have expertise in building Machine learning pipelines and deploy various models

like Forecasting models, Anomaly Detection models, Market Mix Models,

Classification models, Regression models and Clustering Techniques.

• Maintaining Github repositories and cloud computing resources for effective and

efficient version control, development, testing and production.

• Developing proof-of-concept solutions and assisting in rolling these out to our

clients.

Required Skills & Qualifications:

• Hands-on experience with Azure Databricks/ Azure ML/ Azure Synapse, Azure

Blob Storage, and Azure Kubernetes Service (AKS).

• Proficiency in Python (NumPy, Pandas, TensorFlow, PyTorch, Statsmodels, Scikitlearn, Hugging Face, FAISS).
• Hands-on experience with MLflow for tracking and

scaling ML models.

• Expertise in optimising time complexity, memory efficiency, and scalability of ML

models in a cloud environment.

• Experience with Langchain or equivalent and RAG and multi-agentic generation