1490 Machine Learning Architect jobs in Bengaluru

• 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.

About 4flow:

Headquartered in Berlin, Germany, 4flow provides consulting, software and services for logistics and supply chain management. More than 1300 team members leverage their supply chain expertise and IT know-how to best serve their customers at 20+ locations around the world.

4flow develops and implements lean, agile and sustainable supply chain strategies that enhance operational efficiency and drive cost savings for businesses worldwide. Their clients span across multiple high-impact industries including vehicle manufacturers and suppliers, consumer goods and retail, industrial machinery manufacturers, medical technology, basic materials, spare parts, renewable energy, high-tech and telecommunications, and logistics service providers (LSP).

Lead ML Engineer

As a Lead ML Engineer, you will architect and lead the development of advanced machine learning systems and infrastructure. You will guide technical strategy, mentor engineers, and ensure the delivery of scalable, high-impact AI solutions across the organization.

Tasks:

• Lead the design, development, and deployment of production-grade ML models and pipelines
• Define and implement best practices for ML Ops, model monitoring, and lifecycle management
• Collaborate with cross-functional teams to align ML solutions with business and product goals
• Evaluate and integrate LLMs, NLP, and generative AI models into products
• Drive innovation in big data processing using tools like Spark, Databricks, and Delta Live Tables
• Guide the use of cloud platforms (AWS, Azure, GCP) for scalable ML infrastructure
• Mentor junior engineers and foster a culture of technical excellence

Professional Requirements and Expertise:

• 9+ years of experience in ML solution development and deployment
• Bachelor’s or master’s degree in computer science, Machine Learning, Artificial Intelligence, or a related technical field
• Deep expertise in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers
• Strong understanding of machine learning algorithms, data engineering, and ML Ops
• Experience with big data tools like Spark, Databricks, or Delta Live Tables

Good to Have:

• Experience with LLMs & NLP
• Experience with AWS, Azure, or Google Cloud Platform

Personal Skills:

• Visionary and hands-on technical leader
• Strong mentoring and team development capabilities
• Strategic thinker with a proactive mindset
• Ability to work independently and collaboratively within cross-functional teams
• Genuine motivation to contribute to 4flow’s success and alignment with company culture and values

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.

Senior Machine Learning Architect

This is a key position within our company where you will be responsible for designing, building and running large-scale machine learning systems.

• Developing and maintaining advanced machine learning models that power our products
• Designing scalable architectures to support complex AI systems
• Collaborating with cross-functional teams to identify opportunities for improving model accuracy and reducing training time
• Ensuring that machine learning systems are reliable, secure and maintainable
• Participating in system integration testing and contributing to the development of automated testing frameworks

• Expertise in NLP and LAMA Model
• Strong background in AI, ML, GEN-AI and Data Science
• Experience in identifying the right model and training models
• Proficiency in Python Programming

We offer a competitive salary and benefits package, as well as opportunities for career growth and professional development. If you have a passion for machine learning and a desire to make a meaningful impact, we encourage you to apply.

In addition to a stimulating work environment, we also offer:

• A comprehensive health insurance plan
• A retirement savings plan with company match
• Generous paid time off and holidays
• Professional development opportunities and training programs
• A collaborative and dynamic team environment

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.

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.

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.

Principal Machine Learning Engineer

Informatica is on a journey to leverage generative AI to simplify cloud data management. Principal Machine Learning Engineer will be responsible for driving the overall architecture and pipelines to enable Machine Learning engineers to build, train and deploy Models at scale across multiple cloud services providers in a cloud agnostic manner. This role is highly visible and critical to leapfrog Informatica's AI journey.

Responsibilities:

• Design and Implement end to end AI based SaaS for enterprises
• Drive architecture and design for AI and ML related model pipelines, and services
• Collaborate closely with cross-functional internal teams, including stakeholders, to identify opportunities for developing end-to-end AI architectures for diverse industry scenarios.
• Passion for applying state-of-the art AI algorithms to real-world problems.
• Stay up-to-date with the latest developments in AI and related fields, evaluate new developments and technologies for potential integration into existing and future architecture
• Responsible for providing solutions that foster ML Engineer developer productivity.
• Lead the development and deployment of machine learning models, deep learning algorithms, and other AI/ML techniques. Ensure best practices for model training, testing, and validation are followed.

Requirements:

• Solid First Principles thinking for Data and AI
• Solid understanding and hands-on experience developing ML models ranging from regression to deep neural networks including LLMs
• Solid understanding of data engineering principles, adapting data for AI
• Solid understanding of AI/ML frameworks and skills to do rapid prototypes
• Familiarity with modern techniques for Language Understanding, and other Machine Learning and AI technologies
• Collaborate with local and global team of engineers, researchers, and product managers.
• Masters degree in Computer Science, Electrical Engineering or related fields with focus on AI and machine learning.
• 10+ years of industry and research experience in Artificial Intelligence and Machine Learning
• Experience with AWS, Google or Azure is Required
• Experience and understanding of modern ML pipelines using Kubeflow, KServe, Hugging Face, and similar toolkits is preferred.