13,171 Machine Learning Architect jobs in India

Role: AI/ML Architect

Experience: 12+years

Location: Mumbai/Chennai/Indore

Role overview:

- Leads AI and automation strategy.

- Ensures AI is ethically and effectively embedded into enterprise processes.

Key Responsibilities

- Define and lead the AI & automation strategy, ensuring it aligns with business objectives.

- Oversee the development of AI-driven applications, conversational AI, and intelligent automation.

- Implement AI governance and ethics frameworks.

- Lead AI integration with ERP, CRM, ITSM, and enterprise workflows.

- Ensure scalability and optimization of Gen AI models, LLMs, and NLP solutions.

- Partner with data science teams to develop predictive and prescriptive analytics models.

Key Qualifications:

- 12+ years of experience in AI, machine learning, or automation leadership.

- Hands-on experience with Gen AI (LLMs), NLP, RPA, and AI model deployment.

- Strong knowledge of data science, cloud AI services, and automation tools.

- Experience implementing AI at an enterprise scale.

Job Summary: AI/ML Engineer

• Initial Work Location (First 6 Months): Sri City Trade Centre, Central Expressway, Sri City, Andhra Pradesh – ( 70 KM from Chennai )
• After 6 Months: Candidate can continue from either Chennai or Bangalore (Wissen Office)
• Experience: 3–5 years
• Work Mode: Work from Office
• Notice Period: 15 days to 30 days preferred

About the Role

Build, fine-tune, and deploy AI/ML models for intelligent document processing and Generative AI applications. Leverage cutting-edge techniques in NLP, OCR, and LLMs to extract structured data from complex documents and power next-gen AI solutions. As an AI/ML Engineer, you’ll play a key role in transforming unstructured content into actionable insights through scalable, production-ready systems.

Responsibilities

• Develop and optimize machine learning models for document parsing, entity extraction, and information retrieval.
• Work with open-source NLP and visual language models (VLMs) for document structure understanding.
• Implement and fine-tune Generative AI models for various business use cases.
• Build scalable AI pipelines for training and inference.
• Collaborate with cross-functional teams to integrate AI solutions into enterprise applications.
• Stay updated with the latest research in AI/ML and contribute to model improvements.

Qualifications

• Bachelor’s/ Master's degree in Computer Science, Engineering, or related field.
• 3+ years of proven experience as an AI/ML Engineer.

Required Skills

• Hands-on experience with NLP, computer vision, and deep learning frameworks (TensorFlow/PyTorch).
• Experience in fine-tuning transformer-based models (LLMs, VLMs) for document processing.
• Proficiency in Python and ML libraries (Hugging Face, spaCy, OpenCV, etc.).
• Knowledge of cloud platforms (AWS, Azure, GCP) and MLOps best practices.
• Strong problem-solving skills and the ability to work in a fast-paced environment.

At RemoteStar , we're currently hiring for one of our client based in Spain

About client :

Well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. They are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international.

They provide hyper-efficient software to companies seeking to gain an edge with quantum computing and artificial intelligence. Their main products, Singularity and CompactifAI, address critical needs across various industries.

VISA WLL BE PROVIDED BY CLIENT

Joining and Retention bonuses will be provided.

Required Qualifications

• Master’s, or Ph.D. in Computer Science, AI, Data Science, Physics, Math, or a related field. Or equivalent industry experience.
• 4+ years of experience in data science, machine learning, or related roles, with demonstrated experience with NLP or LLMs.
• In-depth knowledge of large foundational model architectures (language and multimodal models) and their lifecycle: training, fine-tuning, alignment, and evaluation.
• Proficient in Python and data tooling ecosystems (Pandas, NumPy, Hugging Face Datasets & Transformers libraries).
• Hands-on experience with text data collection from diverse sources: web scraping, APIs, proprietary corpora, etc.
• Strong understanding of data quality metrics including bias detection, toxicity, and readability.
• Experience working in large shared distributed computing environments, familiarity with relevant tools for hardware optimization (vLLM, TensorRT, NeMo, etc.).
• Experience with version control (git), unit testing, and other fundamental aspects of software development.
• Effective communication and interpersonal abilities.

Preferred Qualifications

• Experience building or contributing to datasets used in LLM pretraining or supervised fine-tuning.
• Experience building foundational LLMs from the ground up
• Familiarity with alignment techniques (e.G., reinforcement learning, preference modeling, reward modeling).
• Exposure to multilingual and low-resource language datasets.
• Contributions to open-source datasets, tools, or publications in dataset-centric research.
• Knowledge of ethical AI, data governance, privacy laws (e.G., GDPR), and responsible data use.
• Familiarity with the software development lifecycle and agile methodologies

As a Senior LLM Engineer, you will

• Design and implement strategies for creating, sourcing, and augmenting datasets tailored for LLM training and fine-tuning.
• Develop scalable pipelines to collect, clean, filter, annotate, and validate large volumes of text data, ensuring quality, ethical compliance, etc.
• Collaborate with ML engineers, researchers, and software engineers to achieve ambitious goals in the preparation of LLMs and complementary work (preparing datasets, model evaluation, model serving, etc.).
• Develop and integrate new routines for modifying and enhancing LLMs, and extending their functionality.
• Make effective use of distributed compute resources and clusters (GPU’s), identify opportunities for further optimization.
• End-to-end preparation of compressed and specialized LLMs for use in production.
• Keep up to date with research trends in LLM foundation models, dataset curation, LLM pretraining data, and benchmarking.
• Contribute to building documentation, development standards, and a healthy shared code base.
• Mentor other engineers and provide knowledge sharing of cutting-edge techniques.

We offer

• Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
• Relocation package (if applicable).
• Up to 9-month contract, ending on June 2026.
• Hybrid role and flexible working hours.
• Be part of a fast-scaling Series B company at the forefront of deep tech.
• Equal pay guaranteed.
• International exposure in a multicultural, cutting-edge environment.

Key Responsibilities:

1. Solution Design: Collaborate with cross-functional teams to define AI use cases, gather requirements, and architect end-to-end AI solutions that align with business goals.

2. Algorithm Development: Develop and implement machine learning and deep learning algorithms, models, and frameworks to solve intricate problems and enhance system capabilities.

3. Data Processing: Oversee data collection, preprocessing, and feature engineering to ensure high-quality input for AI models.

4. Model Training and Evaluation: Train and fine-tune machine learning models using large datasets, and rigorously evaluate model performance using appropriate metrics.

5. Infrastructure and Tools: Design the AI infrastructure, choose suitable frameworks, libraries, and tools, and ensure scalability, reliability, and efficiency of AI systems.

6. Prototyping and POCs: Build rapid prototypes and proof of concepts (POCs) to demonstrate the feasibility and potential of AI solutions.

7. Technical Leadership: Provide technical guidance, mentorship, and support to AI development teams, fostering a culture of innovation and collaboration.

8. Research and Innovation: Stay abreast of AI trends, emerging technologies, and best practices, and contribute to the company's AI strategy by proposing innovative solutions.

9. Deployment and Integration: Lead the deployment of AI solutions into production environments, integrating them with existing systems and workflows.

10. Performance Optimization: Continuously optimize AI solutions for speed, efficiency, and accuracy, and address any bottlenecks or issues.

11. Documentation: Create comprehensive technical documentation, including design specifications, architecture diagrams, and code comments.

Qualifications and Requirements:

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. in AI or Machine Learning is a plus.

- Proven experience as an AI Engineer, Machine Learning Engineer, or AI Architect, with a track record of successful AI solution design and implementation.

- Streamlit -- Python

- Generative AI

- HuggingFace, OpenAi and any Custom Model development experience

- Strong programming skills in languages such as Python, Java, or C++, and proficiency in AI libraries and frameworks (TensorFlow, PyTorch, scikit-learn, etc.).

- In-depth knowledge of machine learning techniques, algorithms, and model evaluation.

- Familiarity with big data technologies, cloud platforms, and distributed computing.

- Excellent problem-solving abilities and analytical thinking.

- Effective communication skills to collaborate with cross-functional teams and present technical concepts to both technical and non-technical stakeholders.

- Demonstrated ability to lead technical projects, drive innovation, and mentor junior team members.

About D Globalist

D Globalist is the world's largest ecosystem of founders looking at geo expansion with a global Business Accelerator support. Being a pioneer in creating the first cross border accelerator, DG is redefining the way businesses are connecting globally.

Your Role

• Integrate AI modules and data engines that power key user workflows
• Work on creating the SaaS platform for companies for cross border expansion support
• Build and manage the initial engineering team (in-house and/or outsourced)
• Work closely with the founding team to translate vision into scalable, secure, and delightful software
• Champion agile development, quality releases, and rapid iterations during alpha, beta, and public launch phases
• Bring a strong product mindset to align tech execution with business outcomes

You’re a Great Fit If You

• Architect scalable AI systems powering DG core modules
• Design data pipelines, model orchestration layers, and AI APIs integrated with the product backend.
• Evaluate, fine-tune, and deploy large language models (OpenAI, Anthropic, Mistral, etc.) for contextual intelligence.
• Collaborate with data scientists, full-stack engineers, and product teams to align architecture with business goals.
• Lead development of embeddings, retrieval systems, and knowledge graphs for founder matchmaking.
• Implement performance monitoring, cost optimization, and safety frameworks for deployed AI models.
• Explore integrations with vector databases, agent frameworks, and proprietary fine-tuning datasets.
• Mentor AI engineers and define best practices for scalable MLops and AI reliability.

Ideal Candidate

• Degree from IIT, IV league or Top Tier College
• 4–8 years of experience in AI/ML engineering or architecture, with hands-on experience in building and deploying LLM-powered systems.
• Expertise in Python, LangChain, OpenAI APIs, Pinecone/Weaviate, FastAPI, TensorFlow/PyTorch.
• Deep understanding of LLM orchestration, embeddings, RAG pipelines, and multi-agent systems.
• Experience architecting data-driven SaaS or recommendation platforms.
• Strong grasp of system design, data privacy, prompt optimization, and API scaling.
• Entrepreneurial mindset - you think like a founder, not an employee.
• Passionate about building AI that solves real-world problems for founders and accelerates global business mobility.

Compensation Structure

Equity & Fixed

Why Join us?

• Join forces with the team behind D Globalist - an established name in global expansion with 1000+ founders, investors, and ecosystem partners across India, Europe, and the US
• Build a first-of-its-kind tech product at the intersection of global business, intelligence, and scale
• Be part of a fast-paced, execution-obsessed team that values trust, autonomy, and ambition

Job Overview

We are seeking a highly skilled and experienced AI/ML, Generative AI Lead to join our prestigious insurance company. The successful candidate will lead a dynamic team of AI/ML professionals, driving the development and implementation of AI and machine learning solutions tailored for the insurance domain. This role is central to our strategy of enhancing operational efficiency, improving customer experience, and pioneering innovative insurance products.

Key Responsibilities

• Leadership and Team Management: Lead, mentor, and manage a team of AI/ML engineers and data scientists, fostering a collaborative and high-performance culture.
• Strategy Development: Develop and implement AI/ML strategies aligned with the company's business goals and objectives.
• AI/ML Solutions: Design, develop, and deploy AI and machine learning models to solve complex problems in underwriting, claims processing, fraud detection, customer service, and personalized marketing.
• Generative AI: Explore and implement generative AI techniques to create novel solutions for product development, risk assessment, and customer engagement.
• Data Management: Oversee the collection, preprocessing, and analysis of large datasets to ensure data quality and integrity.
• Stakeholder Collaboration: Work closely with cross-functional teams, including product managers, actuaries, and IT departments, to ensure successful integration and adoption of AI/ML solutions.
• Research and Innovation: Stay updated with the latest advancements in AI/ML and generative AI, and drive continuous innovation within the team.
• Compliance and Ethics: Ensure all AI/ML solutions comply with industry regulations and ethical standards.
• Performance Monitoring: Implement monitoring and evaluation frameworks to assess the impact and performance of AI/ML models.

Innovation & POC Development

• Lead the development and execution of innovative analytics solutions and Proof-of-Concept (POC) projects.
• Collaborate with cross-functional teams to identify impactful use cases and prototype solutions.

Business Alignment & Outcome Metrics

• Work with business stakeholders to establish success metrics and key performance indicators (KPIs) for analytics initiatives.
• Ensure analytics solutions align with strategic business objectives and regulatory requirements.

POC Adoption & Change Management

• Promote the transition of successful POCs into production environments.
• Develop and implement change management strategies to secure stakeholder support and ongoing usage.

Technical Leadership & Team Oversight

• Provide technical guidance and mentorship to data scientists and analysts.
• Review and approve analytical models, code, and methodologies to ensure their robustness and scalability.

Strategic Research & Future Tech Exploration

• Stay informed about emerging technologies in AI/ML, GenAI, and other relevant future tech for the insurance industry.
• Conduct strategic research and feasibility studies to evaluate potential applications and business impact.

Qualifications

• Education: Master’s in Computer Science, Data Science, Machine Learning, or a related field.
• Experience: Minimum of 5 years of experience in AI/ML, with at least 3 years in a leadership role.
• Technical Skills: Proficiency in programming languages such as Python, R, and Java;
  experience with AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Cloud Tech : Azure, GCP ,AWS. Preferable is Azure
• Domain Knowledge: Expertise in the insurance domain, with a strong understanding of industry-specific challenges and opportunities.
• Analytical Skills: Strong problem-solving skills with the ability to analyze complex data and generate actionable insights.
• Communication Skills: Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders.
• Project Management: Demonstrated experience in managing large-scale AI/ML projects from conception to deployment.
• Innovation: Proven track record of driving innovation and staying abreast of emerging technologies in AI/ML and generative AI.

• Bachelor’s degree in computer science, Data Science, or a related field;
  master’s degree preferred.
• 5+ years of professional and/or postgraduate academic research experience in software engineering.
• 4+ year of experience designing and developing machine learning solutions.
• 3+ years of experience with cloud native engineering, AWS, Azure, Google.

Key Responsibilities:

• Be an expert source on machine learning to drive delivery of new and innovative solutions.
• Propose creative solutions to approach business solutions with emerging technologies.
• Prototype new ways of applying technologies for solving business problems.
• Educate others so that they can demonstrate innovative methods for achieving outcomes.
• Build and maintain machine learning principles, best practices, and code accelerators.
• Conduct external research and internal experimentation for machine learning techniques.
• Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork.
• Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management.

Architect the Future of AI with goML

At goML , we design and build cutting-edge Generative AI, AI/ML solutions that help enterprises unlock the full potential of their data, drive intelligent automation, and create transformative AI-powered experiences.

Our mission is to bridge the gap between advanced AI research and real-world enterprise adoption — empowering businesses to innovate faster, make smarter decisions, and scale AI seamlessly across operations.

We’re looking for an Associate ML Architect with strong expertise in AWS, Generative AI, and ML system design . In this role, you’ll architect scalable, high-performance, and cost-efficient AI solutions — leveraging AWS AI/ML services, modern data platforms, and cloud-native best practices.

If you’re passionate about building production-grade AI systems and driving the next wave of enterprise GenAI innovation, we’d love to hear from you!

Why You? Why Now?

Generative AI is revolutionizing how businesses operate — but scaling it requires strong architecture, security, and performance foundations.

This role is ideal for someone who loves architecting AI/ML workloads , optimizing LLM pipelines , and collaborating with clients to deliver enterprise-grade AI systems.

At goML, You Will:

• Architect and own end-to-end AI/ML and GenAI solutions across industries.
• Collaborate with sales, presales, and engineering teams to define technical proposals.
• Design cloud-native, multi-tenant, and serverless architectures on AWS using services like SageMaker, Bedrock, Lambda, API Gateway, and OpenSearch.
• Work directly with the co-founders and leadership to influence AI/ML strategy and architecture decisions.

What You’ll Do (Key Responsibilities)

First 30 Days: Foundation & Alignment

• Deep dive into goML’s AI/ML & GenAI solution frameworks and ongoing client architectures.
• Familiarize yourself with AWS partnership workflows and solution templates.
• Partner with presales teams to understand client needs and pain points.
• Start designing and reviewing AI/ML workload deployment practices on AWS.

First 60 Days: Execution & Impact

• Own solution design and delivery for client AI/ML and LLM workloads.
• Build reference architectures, POCs , and define ML pipelines with MLOps best practices.
• Optimize inference, embeddings, GPU utilization, and cost efficiency across workloads.
• Collaborate with clients and internal teams to translate GenAI use cases into scalable architectures.

First 180 Days: Ownership & Leadership

• Lead architecture reviews for enterprise-grade AI/ML systems.
• Implement RAG pipelines , fine-tuning strategies, and LLM optimization frameworks.
• Mentor ML engineers and cloud developers in MLOps and scalable AI system design.
• Contribute to goML’s AI/ML best practices , internal accelerators, and knowledge base.
• Represent goML in technical blogs, webinars, and community forums.

What You Bring (Qualifications & Skills)

Must-Have

• 6–7 years of experience in AI/ML solution design and deployment on AWS.
• Proven expertise in AWS AI/ML stack – SageMaker, Bedrock, Lambda, ECS, API Gateway, S3, and DynamoDB.
• Experience in LLMOps, RAG pipelines, and GenAI architecture using models like Claude, Mistral, Llama, or Titan.
• Solid understanding of MLOps , CI/CD, and infrastructure automation (Terraform/CDK).
• Strong communication skills with experience in client-facing discussions and technical proposal creation.

Nice-to-Have

• Exposure to Azure ML, GCP Vertex AI, or NVIDIA AI/ML services.
• Hands-on experience with LangChain, Hugging Face , or vector databases (OpenSearch, Pinecone, FAISS).
• Familiarity with multi-cloud AI deployments and hybrid data architectures.

Why Work With Us?

• Remote-first , with offices in Coimbatore for collaboration and innovation.
• Opportunity to build GenAI and AI/ML systems that power enterprise-scale transformations.
• Direct impact on technical strategy, solution architecture, and client success.