15,416 Machine Learning Specialists jobs in India

Join us as a Machine Learning/Artificial Intelligence Engineer, responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.

To be successful as a Machine Learning/Artificial Intelligence Engineer you should have experience with:

• Good years of experience in IT with background in Development, Machine Learning and/or Data analysis.
• Should have hands-on experience of NLP/AI/ML tool & technologies – GPT, BERT or other language models.
• Should have experience in building GenAI applications, RAG based architectures.
• Experience in Model Development: Research, design, implement, and optimize machine learning models for specific use cases such as predictive analytics, NLP, computer vision, and recommender systems.
• Data Preparation: Collect, preprocess, and analyze large datasets to extract meaningful insights and ensure data quality for model training.
• Deployment: Build and deploy Al/ML solutions into production environments using appropriate tools and frameworks.
• Knowledge of one of the cloud platforms is must : AWS/AZURE.
• Collaboration: Work closely with product managers, data engineers, and software developers to integrate Al capabilities into products and ensure alignment with business objectives.
• Performance Monitoring: Evaluate and monitor model performance and accuracy post-deployment, iterating to address challenges and refine models as needed.
• Strong Affinity to stay informed on the latest trends, tools and research in Al and machine learning space .
• Support and contribute to data collection efforts, as needed.
• Verify data quality to ensure accurate analysis and reporting.
• Help identify the business data needed to produce the most useful insights and future analytics.
• Utilize data to make actionable recommendations at all levels.
• Monitor data management processes to ensure data quality and consistency.
• Monitor system performance, data integrity and usage metrics.
• Contribute to data dictionary, standards, training, and ongoing updates.

Some other highly valued skills may include:

• Web service development experience using REST services/APIs, JSON, XML, IVRs, Jenkins, other Cloud Platforms.
• Experience in setting up DevOps pipelines.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is based in Pune.

Purpose of the role

To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.

Accountabilities

• Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.
• Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.
• Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
• Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth.
• Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
• Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Company Description
MarsDevs is a remote-first, offshore digital product development company based in India.

We specialize in building MVPs, Mobile and Web Applications, SaaS Products, and vertical solutions for SMBs.

With a Track Record Of Delivering Over 60 Solutions In 10 Countries And 12 Different Industry Verticals, We Focus On Quality Code, Speed, And Lasting Technical

• Build and scale Retrieval-Augmented Generation (RAG) systems.
• Fine-tune LLMs for specific use cases and improve performance.
• Develop multi-agent systems using LangChain/LangGraph or other equivalent tools.
• Work with vector databases and scale them using metadata strategies.
• Optimize and deploy transformer-based models.
• Handle large datasets and design efficient data pipelines.
• Address LLM limitations with prompt engineering and fallback logic.
• Collaborate with product, data, and engineering teams to ship AI solutions.
• Stay updated on new tools, research, and apply best-fit :
• Should have 4+ years of experience.
• Experience building large-scale RAG systems.
• Hands-on with LLM fine-tuning and transformers.
• Strong with vector DBs (Pinecone, FAISS, etc.) and metadata filtering.
• Proven experience with multi-agent AI systems.
• Solid Python skills, good grasp of ML fundamentals.
• Experience with LangChain, LangGraph.
• Comfortable deploying on AWS/GCP/Azure.
• Knows LLM limitations and practical workarounds.
• NLP and conversational AI :
• Knowledge of MLOps, model deployment workflows.
• Familiarity with Spark, Ray, or other distributed systems.

)

MI Teams – Sr. AI Engineer

Education:

• BE / BTech or ME in Information Technology / Computer Science Engineering.
• Certifications in Machine Learning / Artificial Intelligence preferred.

Experience & Skills Required (3–5 Years):

• Proven expertise in AI/ML model development and deployment (Regression, Classification, Neural Networks).
• Hands-on experience with Deep Learning (DL), Natural Language Processing (NLP), and LLMs (GPT, LLaMA, HuggingFace models, etc.).
• End-to-end experience in AI/ML projects: data preprocessing, model training, testing, and cloud deployment.
• Strong programming in Python, Java, C, C++.
• Familiarity with DevOps/Agile methodologies, Azure DevOps, Jira, Git.
• Cloud experience with AWS, Azure, or GCP (SageMaker, Vertex AI Studio, Azure AI/ML services).
• Knowledge of API development, integration & security.
• Strong communication and prior client-facing project leadership.

Additional Capability Requirements within AI Teams (Preferred):

• Software Engineering (C, C++, GitHub – mandatory).
• UI & Frontend Development (modern frameworks).
• Backend Engineering with DevSecOps.
• DBMS and Data Encryption expertise.
• System Architecture design & deployment.
• Experience with Docker & Kubernetes.
• Linux Administration.
• Networking – CCNA certified.
• AI/ML Specialists – Python, TensorFlow, R.
• Vision Systems – image/video data handling, compression & decompression.

Job Types: Full-time, Permanent

Pay: Up to ₹1,000,000.00 per year

Benefits:

• Health insurance
• Provident Fund

Work Location: In person

Role Overview :

We are seeking a hands-on AI/ML Lead who will design, develop, and deploy AI-driven lending automation solutions with a focus on NLP workflows, GenAI orchestration, and valuation process automation. This is a 50% coding and delivery role, 50% architecture and leadership role. You will work directly with our Engineering Lead, Data Engineering Team, Product Managers, and UK-based stakeholders to define, architect, and integrate AI capabilities seamlessly into our + React enterprise platform.

Key Responsibilities :

AI Solution Architecture & Development :

• Architect and implement end-to-end AI/ML features aligned with lending workflows :

• NLP Document Parsing OCR, entity extraction, semantic search, summarization, classification.

• Valuation Automation Predictive modeling for asset and loan valuations.

• GenAI Orchestration Multi-step, multi-service automation workflows.

• Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures.

• Integrate GenAI APIs (OpenAI GPT, Anthropic Claude, AWS Comprehend, Google Vertex AI, etc.) into existing systems.

Model Lifecycle Management :

• Select, train, fine-tune, and deploy models (LLMs, transformer-based models, classical ML).

• Implement model monitoring pipelines for accuracy, drift detection, bias evaluation, and retraining triggers.

• Optimize inference latency, throughput, and scalability for production workloads.

Data Readiness & Governance :

• Collaborate with Data Engineering to ensure AI-ready data pipelines (schema design, storage format, vectorization strategies).

• Establish data labeling, augmentation, and versioning processes for supervised and semi-supervised learning.

• Ensure compliance with data privacy regulations (GDPR, RBI guidelines) and ethical AI principles.

AI Workflow Orchestration :

• Design and implement multi-step AI orchestration layers combining LLM prompts, RAG (Retrieval-Augmented Generation), and business rules.

• Build custom prompt chains and tools to handle complex workflows like Credit Committee Pack creation and communication parsing.

Stakeholder Collaboration & Leadership :

• Translate complex AI concepts into clear business benefits for non-technical stakeholders.

• Mentor and guide developers on AI integration best practices.

• Track AI feature KPIs and demonstrate measurable business impact.

Required Skills & Experience :

• Total Experience : years in software engineering, with 3+ years hands-on AI/ML solution delivery.

• Proven record of deploying AI/NLP features in production environments.

• Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow).

• Strong experience with NLP pipelines tokenization, embeddings, semantic search, summarization, classification, sentiment analysis.

• Expertise in AI orchestration frameworks (LangChain, Haystack, LlamaIndex) and workflow automation.

• Proficient in REST API design, microservices, and integrating AI with JavaScript/TypeScript-based backends.

• Deep understanding of data structures, feature engineering, and vector databases (Pinecone, Weaviate, FAISS).

• Solid grasp of MLOps tools (MLflow, Kubeflow, AWS SageMaker, Azure ML).

• Familiarity with cloud-native AI deployments (AWS, Azure, GCP).

• Strong communication skills for technical-to-business translation.

Bonus Skills :

• Fintech or lending automation platform experience.

• Familiarity with financial document workflows (KYC, underwriting, valuation reports).

• Hands-on experience with RAG pipelines, prompt engineering, and custom LLM training.

Key Responsibilities

• Design, develop, and deploy scalable machine learning models for classification, regression, NLP, and generative AI tasks.
• Build and optimize data transformation workflows using Python, Pandas, and related libraries.
• Lead AI/ML pipelines from data ingestion to model deployment, monitoring, and retraining.
• Implement model observability and monitoring for drift detection and continuous evaluation.
• Develop and deploy REST APIs to integrate ML models with production systems using frameworks like FastAPI.
• Ensure high code quality through unit/integration testing and code reviews.
• Collaborate with cross-functional teams including Data Engineers, DevOps, and Product Managers.
• Stay updated with the latest advancements in AI, ML, and GenAI frameworks and tools.
• Apply DevOps/MLOps practices to automate and manage the full ML lifecycle.

Required Skills
Programming & Python Ecosystem :

• Advanced proficiency in Python with expertise in Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Strong understanding of asynchronous programming, concurrency, and FastAPI (Starlette).
• In-depth knowledge of multithreading, multiprocessing, and Python GIL.
• Ability to write clean, efficient, and testable code.

Machine Learning & Deep Learning

• Strong grasp of traditional ML concepts : classification, regression, regularization (L1/L2), overfitting/underfitting, multicollinearity.
• Experience with deep learning architectures : RNNs, attention mechanisms, dropout, early stopping, GANs, diffusion models.
• Knowledge of transfer learning and pre-trained model fine-tuning.

MLOps

• Hands-on experience in ML pipeline design including training, deployment, and monitoring.
• Proficiency in data drift and concept drift detection and mitigation.
• Familiarity with model observability tools, unstructured data drift monitoring, and automated drift alerts.

Software Engineering & DevOps

• Strong expertise in REST API development, CI/CD pipelines, and integration testing.
• Experience with Docker and containerized deployments.
• Familiarity with cloud-based ML deployment (AWS, Azure) and logging/monitoring frameworks.

Data Engineering & Problem Solving

• Strong experience with data wrangling, transformation, joins, ranking, filtering, and preprocessing using Python/Pandas.
• Ability to handle large datasets and build efficient preprocessing workflows.

Nice-to-Have

• Experience in Generative AI and working with LLMs.
• Exposure to MLOps tools like MLflow, Kubeflow, or Airflow.
• Knowledge of transformer-based models, embeddings, and NLP pipelines.
• Prior contributions to open-source ML frameworks or GitHub repositories.

Core Skills & Proficiency

• Python
• NumPy
• PyTorch
• Machine Learning
• Deep Learning
• REST API Development
• Agile Software Development
• API Development
• Generative AI
• Artificial Intelligence

)

Job Description : AI Engineer
Overview
We are looking for a highly skilled and experienced AI/ML to join our dynamic team. The ideal candidate will have a robust background in developing web applications using Django and Flask, with expertise in deploying and managing applications on AWS. Proficiency in Django Rest Framework (DRF), a solid understanding of machine learning concepts, and hands-on experience with tools like PyTorch, TensorFlow, and transformer architectures are essential.

Key Responsibilities

• Develop and maintain web applications using Django and Flask frameworks.
• Design and implement RESTful APIs using Django Rest Framework (DRF).
• Deploy, manage, and optimize applications on AWS services, including EC2, S3, RDS, Lambda, and CloudFormation.
• Build and integrate APIs for AI/ML models into existing systems.
• Create scalable machine learning models using frameworks like PyTorch, TensorFlow, and scikit-learn.
• Implement transformer architectures (e.g., BERT, GPT) for NLP and other advanced AI use cases.
• Optimize machine learning models through advanced techniques such as hyperparameter tuning, pruning, and quantization.
• Deploy and manage machine learning models in production environments using tools like TensorFlow Serving, TorchServe, and AWS SageMaker.
• Ensure the scalability, performance, and reliability of applications and deployed models.
• Collaborate with cross-functional teams to analyze requirements and deliver effective technical solutions.
• Write clean, maintainable, and efficient code following best practices.
• Conduct code reviews and provide constructive feedback to peers.
• Stay up-to-date with the latest industry trends and technologies, particularly in AI/ML.

Required Skills And Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proficient in Python with a strong understanding of its ecosystem.
• Extensive experience with Django and Flask frameworks.
• Hands-on experience with AWS services for application deployment and management.
• Strong knowledge of Django Rest Framework (DRF) for building APIs.
• Expertise in machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Experience with transformer architectures for NLP and advanced AI solutions.
• Solid understanding of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Familiarity with MLOps practices for managing the machine learning lifecycle.
• Basic knowledge of front-end technologies (e.g., JavaScript, HTML, CSS) is a plus.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.

)

AI/ML Lead Lending Automation & GenAI Orchestration

Role Type : Full-time | Hands-On AI/ML Leadership

Work Location : Hyderabad

Role Overview :

We are seeking a hands-on AI/ML Lead who will design, develop, and deploy AI-driven lending automation solutions with a focus on NLP workflows, GenAI orchestration, and valuation process automation. This is a 50% coding and delivery role, 50% architecture and leadership role. You will work directly with our Engineering Lead, Data Engineering Team, Product Managers, and UK-based stakeholders to define, architect, and integrate AI capabilities seamlessly into our + React enterprise platform.

Key Responsibilities :

AI Solution Architecture & Development :

• Architect and implement end-to-end AI/ML features aligned with lending workflows :

• NLP Document Parsing OCR, entity extraction, semantic search, summarization, classification.

• Valuation Automation Predictive modeling for asset and loan valuations.

• GenAI Orchestration Multi-step, multi-service automation workflows.

• Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures.

• Integrate GenAI APIs (OpenAI GPT, Anthropic Claude, AWS Comprehend, Google Vertex AI, etc.) into existing systems.

Model Lifecycle Management :

• Select, train, fine-tune, and deploy models (LLMs, transformer-based models, classical ML).

• Implement model monitoring pipelines for accuracy, drift detection, bias evaluation, and retraining triggers.

• Optimize inference latency, throughput, and scalability for production workloads.

Data Readiness & Governance :

• Collaborate with Data Engineering to ensure AI-ready data pipelines (schema design, storage format, vectorization strategies).

• Establish data labeling, augmentation, and versioning processes for supervised and semi-supervised learning.

• Ensure compliance with data privacy regulations (GDPR, RBI guidelines) and ethical AI principles.

AI Workflow Orchestration :

• Design and implement multi-step AI orchestration layers combining LLM prompts, RAG (Retrieval-Augmented Generation), and business rules.

• Build custom prompt chains and tools to handle complex workflows like Credit Committee Pack creation and communication parsing.

Stakeholder Collaboration & Leadership :

• Translate complex AI concepts into clear business benefits for non-technical stakeholders.

• Mentor and guide developers on AI integration best practices.

• Track AI feature KPIs and demonstrate measurable business impact.

Required Skills & Experience :

• Total Experience : years in software engineering, with 3+ years hands-on AI/ML solution delivery.

• Proven record of deploying AI/NLP features in production environments.

• Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow).

• Strong experience with NLP pipelines tokenization, embeddings, semantic search, summarization, classification, sentiment analysis.

• Expertise in AI orchestration frameworks (LangChain, Haystack, LlamaIndex) and workflow automation.

• Proficient in REST API design, microservices, and integrating AI with JavaScript/TypeScript-based backends.

• Deep understanding of data structures, feature engineering, and vector databases (Pinecone, Weaviate, FAISS).

• Solid grasp of MLOps tools (MLflow, Kubeflow, AWS SageMaker, Azure ML).

• Familiarity with cloud-native AI deployments (AWS, Azure, GCP).

• Strong communication skills for technical-to-business translation.

Bonus Skills :

• Fintech or lending automation platform experience.

• Familiarity with financial document workflows (KYC, underwriting, valuation reports).

• Hands-on experience with RAG pipelines, prompt engineering, and custom LLM training.

develop and manage applications involved with Search Systems. Maintain and upgrade search indices for large document repositories, as well as optimizing indexing/queries and supporting analytics

Analyze website metrics and customer behaviour data