184 Machine Learning Engineer jobs in Indore

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.

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.

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.

Job Details:

Position: ML Engineer

Experience: 7-10 years

Work Mode: Remote

Notice Period: Immediate Joiner – 15 days

Job Summary:

We are looking for highly motivated and experienced Machine Learning Engineers to join our

advanced analytics and AI team. The ideal candidates will have strong proficiency in building,

training, and deploying machine learning models at scale using modern ML tools and

frameworks. Experience with LLMs (Large Language Models) such as OpenAI and Hugging

Face Transformers is highly desirable

Must Have: DevOps tools, Python and Excellent Communication

Key Responsibilities:

• Design, develop, and deploy machine learning models for real-world applications.

• Implement and optimize end-to-end ML pipelines using PySpark and MLflow.

• Work with structured and unstructured data using Pandas, NumPy, and other data processing

libraries.

• Train and fine-tune models using scikit-learn, TensorFlow, or PyTorch.

• Integrate and experiment with Large Language Models (LLMs) such as OpenAI GPT,

Hugging Face Transformers, etc.

• Collaborate with cross-functional teams including data engineers, product managers, and

software developers.

• Monitor model performance and continuously improve model accuracy and reliability.

• Maintain proper versioning and reproducibility of ML experiments using MLflow

Required Skills:

• Strong programming experience in Python.

• Solid understanding of machine learning algorithms, model development, and evaluation

techniques.

• Experience with PySpark for large-scale data processing.

• Proficient with MLflow for tracking experiments and model lifecycle management.

• Hands-on experience with Pandas, NumPy, and Scikit-learn.

• Familiarity or hands-on experience with LLMs (e.g., OpenAI, Hugging Face Transformers).

• Understanding of MLOps principles and deployment best practices

Preferred Qualifications:

• Bachelor’s or master's degree in computer science, AI/ML, Data Science, or a related field.

• Experience in cloud ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) is a plus

• Strong analytical and problem-solving abilities.

• Excellent communication and teamwork skills.

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:

• Design, develop, and implement machine learning algorithms and models using Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Collaborate with data scientists and software engineers to integrate ML models into production systems.
• Preprocess, clean, and transform large datasets to prepare them for model training.
• Evaluate model performance, identify areas for improvement, and implement optimization techniques.
• Develop and maintain robust data pipelines for training and inference.
• Stay current with the latest research and advancements in machine learning and artificial intelligence.
• Build and manage ML infrastructure, including model deployment and monitoring tools.
• Conduct A/B testing and other experiments to validate model effectiveness.
• Communicate complex findings and model behaviors to technical and non-technical stakeholders.
• Contribute to the development of best practices for ML development and deployment.

• Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related quantitative field.
• Proven experience (3+ years) in developing and deploying machine learning models in a production environment.
• Strong proficiency in Python and its data science ecosystem (NumPy, Pandas, Matplotlib).
• Expertise in machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of algorithms, data structures, and software engineering principles.
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Familiarity with big data technologies (e.g., Spark, Hadoop).
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills, essential for a remote team environment.
• Experience with MLOps practices and tools is a plus.