465 Machine Learning jobs in Noida

Role Overview

We are looking for an experienced MLOps Lead with deep expertise in Azure and AWS cloud ecosystems, who can design, deploy, and manage scalable AI/ML infrastructure. The ideal candidate should bring a strong background in cloud governance, GenAI tooling, automation, and CI/CD pipelines, with hands-on experience across modern MLOps frameworks.

Key Responsibilities

• Design, implement, and manage scalable cloud-based AI/ML infrastructure across Azure and AWS.
• Drive end-to-end MLOps lifecycle — model deployment, monitoring, retraining, and governance.
• Enable GenAI and Agentic AI platforms leveraging Azure OpenAI, Bedrock, Anthropic Claude, LangChain, etc.
• Implement CI/CD pipelines using Azure DevOps or AWS CodePipeline.
• Ensure security, observability, and compliance across ML and GenAI ecosystems.
• Manage infrastructure automation via Terraform, Bicep, CloudFormation, or similar IaC tools.
• Collaborate with data science and engineering teams to optimize ML workflows, data pipelines, and API integrations.
• Implement monitoring and alerting using Grafana, Prometheus, Azure Monitor, and Application Insights.
• Oversee networking, identity management, and role-based access controls (IAM, RBAC) across clouds.
• Support model lifecycle management — drift monitoring, retraining, technical evaluation, and business validation.

Technical Skills & Expertise

Cloud & MLOps Platforms

• Azure: Azure ML, Azure AI Services, Azure OpenAI, Azure Kubernetes Service (AKS), Databricks, Azure Search, Azure Blob, Cosmos DB, Azure SQL, Azure Functions, Azure Event Hub, Azure Resource Manager (ARM), Bicep.
• AWS: SageMaker, Bedrock, Lambda, DynamoDB, S3, RDS, Redshift, ECR, CloudFormation, CDK, KMS, EventBridge, Step Functions.

AI/ML & Programming

• Hands-on in Python, with exposure to TensorFlow, PyTorch, scikit-learn.
• Understanding of LLM tokenization, prompt injection risks, jailbreak prevention, and AI safety techniques.
• Familiarity with LangChain, LlamaCloud, AI Foundry, and related frameworks.
• Experience in model monitoring, retraining, and evaluation workflows.

DevOps & Infrastructure

• Expertise in CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure automation.
• Strong in governance, audit logging, security policies (Azure Policy, AWS SCP, IAM).
• Deep understanding of networking, DNS, load balancers, VNets/VPCs, VPNs.
• Skilled in IaC tools – Terraform, Bicep, ARM, CloudFormation.

Monitoring & Observability

• Experience with Grafana, Prometheus, Application Insights, Log Analytics Workspaces, Azure Monitor.

Security & Access Management

• Understanding of Microsoft AD, least privilege principles, IAM, RBAC.

Testing & Automation

• Familiarity with unit testing and integration testing in CI/CD workflows (preferably Azure DevOps).

Good to Have

• Experience with Azure Bot Framework, M365 Copilot, and APIM.
• Exposure to code assistants such as GitHub Copilot, Cursor, Claude Code.
• Knowledge of Boto3 SDK (AWS Python) and TypeScript for IaC.

Preferred Background

• Strong background in cloud infrastructure engineering and machine learning operations.
• Proven ability to lead cross-functional teams and implement AI governance at scale.
• Excellent problem-solving, communication, and documentation skills.

Branch Overview

Branch delivers world-class financial services to the mobile generation. With offices in the United States, Nigeria, Kenya, and India, Branch is a for-profit socially conscious company that uses the power of data science to reduce the cost of delivering financial services in emerging markets. We believe that everyone everywhere deserves fair financial access. The rapid spread of smartphones presents an opportunity for the world's emerging middle class to access banking options and achieve financial flexibility.

Branch's mission-driven team is led by the founder and former CEO of Kiva.org. The company presents a rich opportunity for our team members to drive meaningful growth in rapidly evolving and changing markets. In 2019, Branch announced our Series C and garnered more than $100M in funding with investments from leading Silicon Valley firms, including Andreessen Horowitz, Trinity Capital, Foundation Capital, Visa, and the International Finance Corporation (IFC).

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As a product-driven org, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we create an environment where everyone feels empowered to propose solutions to the challenges we face.

We value diversity and are committed to providing an inclusive working environment where human beings of all backgrounds can thrive.

Job Overview

Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.

Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.

Responsibilities

• Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.
• Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.
• Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.
• Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.

Qualifications

• 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.
• Excellent software engineering and programming skills, especially Python and SQL.
• A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.
• A deep understanding of using cloud computing infrastructure and data pipelines in production.
• Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.
• Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.
• The drive to make a positive impact on customers' lives.

Benefits of Joining

• Mission-driven, fast-paced, and entrepreneurial environment
• Competitive salary and equity package
• A collaborative and flat company culture
• Fully-paid Group Medical Insurance and Personal Accidental Insurance
• Unlimited paid time off, including personal leave, bereavement leave, and sick leave
• Fully paid parental leave — 6 months maternity leave and 3 months paternity leave
• Monthly WFH stipend alongside a one-time home office set-up budget
• $500 Annual professional development budget
• Team meals and social events — Virtual and In-person

We're looking for more than just qualifications -- if you're unsure that you meet the criteria but identify with our vision of providing equal opportunity to everyone to access financial services, please do not hesitate to apply

Branch International is an Equal Opportunity Employer. The company does not and will not discriminate in employment on any basis prohibited by applicable law.

Job Role: ML Engineer

Experience: 6-12 Years

Location: Pune, Bangalore, Hyderabad, Trivandrum, Chennai, Kochi, Gurgaon, Noida

Key Summary:

● The MLE will design, build, test, and deploy scalable machine learning systems,

optimizing model accuracy and efficiency

● Model Development: Algorithms and architectures span traditional statistical methods to

deep learning along with employing LLMs in modern frameworks.

● Data Preparation: Prepare, cleanse, and transform data for model training and

evaluation.

● Algorithm Implementation: Implement and optimize machine learning algorithms and

statistical models.

● System Integration: Integrate models into existing systems and workflows.

● Model Deployment: Deploy models to production environments and monitor

performance.

● Collaboration: Work closely with data scientists, software engineers, and other

stakeholders.

● Continuous Improvement: Identify areas for improvement in model performance and

systems.

Skills:

● Programming and Software Engineering: Knowledge of software engineering best

practices (version control, testing, CI/CD).

● Data Engineering: Ability to handle data pipelines, data cleaning, and feature

engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for

troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch,

Neo4J graph

● Model Deployment and Monitoring: MLOps Experience in deploying ML models to

production environments.

● Knowledge of model monitoring and performance evaluation.

Required experience:

● Amazon SageMaker: Deep understanding of SageMaker's capabilities for building,

training, and deploying ML models; understanding of the Sagemaker pipeline with ability

to analyze gaps and recommend/implement improvements

● AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in

ML workflows

● AWS data: Redshift, Glue

● Containerization and Orchestration: Understanding of Docker and Kubernetes, and their

implementation within AWS (EKS, ECS)

Skills:

Aws, Aws Cloud, Amazon Redshift, Eks

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.

Key Responsibilities:

• Design and develop generative AI models using techniques like RAG, transformers, and other relevant approaches.
• Fine-tune pre-trained LLMs for specific tasks and domains.
• Conduct research on new techniques for improving the performance and capabilities of generative AI models.
• Apply software engineering rigor and best practices to machine learning /Generative AI pipelines.
• Evaluate and analyse the performance of ML/generative AI models.
• Stay up to date on the latest advancements in generative AI research.
• Facilitate the development and deployment of proof-of-concept Generative AI systems.

Qualifications:

• Bachelor's/Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 3-5 years of experience in generative AI or related fields.
• Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance.
• Strong programming skills in Python.
• Familiarity with RAG and other techniques for building generative models.
• Extensive experience with Git, Docker and a good understanding of Linux for managing servers.
• Experience with cloud-based ecosystems, especially AWS ML/GenAI services.
• Exposure to ML/GenAI frameworks and tools.
• Excellent communication and collaboration skills.
• Ability to work independently and in a team-oriented environment.
• Methodical and meticulous towards work and planning.

Transforming mental health support, we aim to bridge accessibility gaps. With instant and private 24/7 support, we address significant wait times for therapists.

This pivotal role shapes mental health technology by leading the end-to-end model lifecycle of our conversational AI:

1. Problem framing
2. Data curation
3. Modeling, fine-tuning, and post-training
4. Evaluations
5. Rollout and monitoring

You'll design agentic flows (tool use, planning, multi-turn memory) and safe retrieval for mental-health use cases.

Implement alignment & safety layers (e.g., self-harm detection, red-teaming, refusal strategies, escalation paths) tuned to clinical guidelines.

Optimize for latency, cost, and quality.

As a seasoned AI Engineer, you will be responsible for designing and implementing cutting-edge machine learning systems at scale.

The ideal candidate should have 4-10 years of experience in Artificial Intelligence and Machine Learning, with a strong background in NLP, LAMA Model, AI, ML, GEN-AI, MACHINE LEARNING (ML), Data Science, Statistical modeling, and Python Programming.

• Designing, building, and running machine learning systems at scale
• Maintaining the infrastructure that supports the models and algorithms
• Improving model accuracy by tweaking parameters or updating data
• Developing and maintaining a platform for automating ML model creation, training, deployment, and updates
• Collaborating with customers on product documentation
• Participating in trouble report reviews and analysis
• Conducting system integration testing

Job Title: AI/ML Engineer

Location: UAE (Remote)

Experience Range: 5 to 8 Years

Responsibilities:

• Develop prompt engineering strategies
• Specify ML methodologies for demo scenarios
• Implement AI/ML components where applicable
• Optimize model performance for demo environments

Ideal Qualifications:

• 5+ years ML engineering experience
• Expertise in prompt engineering and LLMs
• Experience with ML frameworks

Interested? To apply, please send your resume to Ankita Rathod

Email address:

Senior Software Engineer – Machine Learning (Hybrid/Remote)

Are you an exceptional technologist ready to take your AIML expertise to the next level? Join a growing agile technology team shaping innovative solutions for the life science regulatory affairs domain.

About the Role

This is a pivotal position for an experienced software engineer specialising in AI/ML development, offering technical autonomy, impactful responsibilities, and opportunities for growth. You'll build scalable, secure, and robust systems that drive business value and contribute directly to our technology roadmap and engineering culture.

Key Responsibilities

• Develop and deploy scalable microservices, ensuring independent and reliable delivery.
• Collaborate closely with cross-functional teams including front-end, DevOps, and product to deliver high-quality software.
• Drive code excellence with rigorous unit/integration testing and code reviews.
• Monitor, debug, and optimize backend systems for enterprise-grade performance.
• Design high-performance, fault-tolerant systems capable of handling complex data workflows.
• Lead knowledge sharing, clear communication, and documentation for technical solutions.
• Coordinate effectively with remote global team members.
• Develop robust, scalable web applications tailored for B2B and enterprise client needs.
• Required Skills and Experience
• 7+ years building production-grade AIML systems (Python).
• Deep proficiency in LLM frameworks: LangChain, LlamaIndex, and custom RAG (Retrieval-Augmented Generation) pipelines.
• Strong background with vector databases and semantic search (Pinecone, Weaviate, FAISS, ChromaDB).
• Advanced prompt engineering and LLM fine-tuning for regulatory and compliance domains.
• NLP expertise: document processing, multi-format parsing (PDF, HTML, XML, Word), semantic embeddings.
• Hands-on work with Hugging Face Transformers (BERTRoBERTa, NER, text classification).
• Familiarity with LLM providers (OpenAI GPT-4, Anthropic Claude, Azure OpenAI, Llama, Mistral).
• Extensive cloud experience (AWS, Azure, Google Cloud Platform).
• Python async frameworks (FastAPI, asyncio, aio RESTful API design, JSON, OpenAPI/Swagger.
• Skilled with CI/CD tools (GitHub Actions, Jenkins, CodePipeline) and containerization (Docker, Kubernetes)(1).
• Advanced database skills: PostgreSQL, MySQL, query optimization, indexing, schema design; NoSQL experience (MongoDB, DynamoDB).
• Git version control mastery, including complex workflows and resolution strategies.
• Familiarity with IaC tools (CloudFormation, Terraform).

Qualifications

• Bachelors/Masters in Computer Science or related field.
• Track record of backend development in complex, scalable applications.
• Strong communication, collaboration, and stakeholder management skills(1).
• Experience with healthcare IT systems (HIS, EMR/EHR) and knowledge of data privacy regulations (HIPAA, GDPR) is a plus.
• Cloud certifications and experience with AI-assisted development tools (GitHub Copilot) are highly desirable.

Soft Skills

• Analytical thinking and problem-solving ability.
• Capable of working independently and leading technical discussions.
• Adaptable to fast-paced, agile environments.

What's Offered

Competitive salary and benefits.

Flexible hours, remote work options, and a collaborative, people-centred team.

Opportunities to drive cutting-edge projects in the life science regulatory space.

Supportive environment for professional development and growth.

Sony Research India is driving cutting-edge research and development in various locations around the globe, including laboratories in Japan, the United States, Europe, and Asia. We endeavor to create new technology, products, and services while sustaining Sony Group's diverse businesses in electronics, entertainment, and financial fields. For our research centre to blaze a trail in the latest technologies, we seek to foster the growth of a diverse pool of research and engineering talent and create a technology talent bank to drive research excellence worldwide. Sony Research India is offering outstanding career opportunities around frontline technologies such as AI and data analytics.

We are looking for a highly motivated research consultant who can assist in our research and development efforts on large-scale user engagement predictive models. The ideal candidate should have prior experience in Deep Learning, Natural Language Processing.

Key Responsibility:

• Developing models to analyze user behavior patterns on OTT platforms and predicting their likelihood of leaving, along with plausible reasons behind their behavior.

• Building causal inference–based intervention models aimed at retaining users on the platform.

• Contributing to developing and evaluating models (including user engagement foundation model) leveraging pre-trained LLMs.

• Work closely with other research scientists, engineers, and product teams fostering a collaborative and intellectually stimulating environment.

• Contribute to millions of OTT platform users towards improving their experience by leveraging AI capabilities.

• Contribute to the research community by sharing insights and participating in external academic workshops and conferences.

Work Location:

• Remote within India,

Duration of the paid contractual role:

• The annual paid direct contractual tenure is extendable.
• Ideally this position will start from first week of November 2025.
• The working hours are from 9:00 to 18:00 (Monday to Friday) full-time.

Essential Education:

• Candidates who have successfully completed Ph.D./Master degree preferably from CS/AI/ML (recommendation, foundational models etc.) academic background.

Must Have Skills & Abilities:

• A strong background in applied deep learning and machine learning, both in terms of conceptual understanding, as well as practical experience.
• A good understanding on handling large scale datasets with SQL.
• Understanding about current start of the art machine learning literature.
• Prior experience in developing large scale prediction and reasoning models.
• Strong knowledge and interest in LLMs (fine-tuning, training and using LLMs).
• Proficiency in hands-on with Python and one or more popular deep learning framework.
• Ability to envision new ideas and proving them through theory and/or experiments.
• Knowledge of working on any cloud platform, preferably AWS, is desirable.

Good to Have Skills:

• PhD candidates with thesis in the area of causal inference is highly preferred.
• 0-1 year of work experience in building and deploying large-scale predictive models in production.
• 0-1 year of work experience in LLM/NLP projects within a start-up environment.
• Good publication record, with publications in major machine learning conferences (e.g. NeurIPS, ICML, KDD, AAAI, SIGIR, RecSys, WSDM, ICDM, ECML, etc.).

Our Values:

• Dreams & Curiosity: Pioneer the future with dreams and curiosity.
• Diversity: Pursue the creation of the very best by harnessing diversity and varying viewpoints.
• Integrity & Sincerity: Earn the trust for Sony brand through ethical and responsible conduct.
• Sustainability: Fulfil our stakeholder responsibilities through disciplined business practices.

Sony Research India is committed to equal opportunity in all its employment practices, policies and procedures and to ensuring that no worker or potential worker will receive less favourable treatment due to any characteristic protected under applicable local laws.