229 AI Software Engineer jobs in Kakinada

Openings : Senior and Mid-Level

Location : Remote in India

Hours : IST

Rate: 25-35 LPA

Job Purpose

Analyzing, designing, developing and managing the data pipelines to release scalable Data Science models. The ML/Ops Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated and repeatable way.

Job Responsibilities

• Create and maintain a scalable code to deliver AI/ML processes.
• Design and implement the pipelines for building and deployment of ML models.
• Design dashboards to monitor a system.
• Collect metrics and create alerts based on them.
• Design and execute performance tests.
• Perform feasibility studies/analysis with a critical point of view.
• Support and maintain (troubleshoot issues with data and applications).
• Develop technical documentation for applications, including diagrams and manuals.
• Working on many different software challenges always and ensuring a combination of simplicity and
• maintainability within the code.
• Contribute to architectural designs of large complexity and size, potentially involving several distinct
• software components.
• Work as a member of a team, encouraging team building, motivation and cultivating effective team
• relations.

Required Experience

• Demonstrated experience and knowledge in Linux and Docker containers
• Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS)
• Proficient in programming languages: Python
• Experience with ML/Ops technologies like Azure ML
• Experience with SQL
• Experience in the use of collaborative developing tools such as Git, Confluence, Jira, etc.
• Strong ability to analyze and synthesize. (Good analytical and logical thinking capability)
• Proactive attitude, resolutive, used to work in a team and manage deadlines.
• Ability to learn quickly
• Agile methodologies development (SCRUM/KANBAN).
• Minimal work experience of 6 years with evidence.
• Ability to keep fluid communication written and oral in English, both written and spoken

Preferred Experience

• Demonstrated experience and knowledge in unit and integration testing
• Experience or Exposure with AI/ML frameworks: PyTorch, Onnx, Tensorflow
• Experience designing and implementing CICD pipelines for automation.
• Experience designing monitoring dashboards (Grafana or similar)

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 Title: Machine learning engineer Lead

Location: Hybrid Role / Chennai / Bangalore

Type: Fulltime with our client

Job Required Skills:

· 5+ years experience

· College degree

· Strong proficiency in Python (bonus if also have one of these Java, Scala, etc.).

· Advanced experience in SQL; Familiarity with version control tools (Git etc.).

· Understanding of statistical, machine learning and deep learning algorithms.

Ø Manage processes

Ø Has done computer science work, technology work and analysis work – needs a good blend of this

Ø Someone to actual do the work – make improvements to processes and do the work, not just suggest/talk/plan

· Experience working with big data environments using technologies such as Spark, Flink, NoSQL DB structures.

· Experience in cloud computing technologies based analytic solutions.

• · Experience building and productionizing micro-services and REST APIs.

Key Responsibilities:

• Design and implement modular, reusable AI agents capable of autonomous decision-making using LLMs, APIs, and tools like LangChain, AutoGen, or Semantic Kernel.
• Engineer prompt strategies for task-specific agent workflows (e.g., document classification, summarization, labeling, sentiment detection).
• Integrate ML models (NLP, CV, RL) into agent behavior pipelines to support inference, learning, and feedback loops.
• Contribute to multi-agent orchestration logic including task delegation, tool selection, message passing, and memory/state management.
• Collaborate with MLOps, data engineering, and product teams to deploy agents at scale in production environments.
• Develop and maintain agent evaluations, unit tests, and automated quality checks for reliability and interpretability.
• Monitor and refine agent performance using logging, observability tools, and feedback signals.

Required Qualifications:

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field.
• 3+ years of experience in developing AI/ML systems; 1+ year in agent-based architectures or LLM-enabled automation.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn).
• Experience with LLM frameworks (LangChain, AutoGen, OpenAI, Anthropic, Hugging Face Transformers).
• Strong grasp of NLP, prompt engineering, reinforcement learning, and decision systems.
• Knowledge of cloud environments (AWS, Azure, GCP) and CI/CD for AI systems.

Preferred Skills:

• Familiarity with multi-agent frameworks and agent orchestration design patterns.
• Experience in building autonomous AI applications for data governance, annotation, or knowledge extraction.
• Background in human-in-the-loop systems, active learning, or interactive AI workflows.
• Understanding of vector databases (e.g., FAISS, Pinecone) and semantic search.

Position- Machine Learning Engineer

Experience - 3 to 5 years

Job Location - Pune / Remote

Immediate Joiner Only

Role Overview

The ML Ops Engineer plays a critical role in the development, automation, and deployment of Machine Learning (ML) and Generative AI (GenAI) pipelines across AWS cloud environments. This hands-on role emphasizes building reproducible workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports AI systems deployed in banking environments, where resilience and reliability are paramount.

Key Experience:

• 3-5 years Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks (e.g., scikit-learn).
• Should have used Python in ML domain to build, train and maintain models.
• Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock.
• Experience with container workflows (Docker) and model lifecycle management.
• Foundational knowledge of observability practices and model deployment fundamentals.
• Interest or experience in supporting AI systems used by developers or analysts.
• Strong communication and documentation skills with a collaborative team mindset.
• Ability to assume ownership of assignments and consistently meet deadlines.

Responsibilities :

• Deploy and maintain ML and GenAI models using AWS services, including SageMaker, Fargate, and Bedrock.
• Apply prompt engineering techniques to optimize GenAI model performance and reliability.
• Experience with Retrieval-Augmented Generation (RAG) applications is a plus.
• Assist in building and maintaining internal model-serving platforms to support development teams.
• Implement containerized services using Docker and deploy them to AWS infrastructure.
• Write Infrastructure-as-Code (IaC) using Terraform to automate cloud resource provisioning (nice to have ).
• Participate in unit and end-to-end testing of ML pipelines, services, and monitoring workflows.
• Support model monitoring and health tracking using AWS CloudWatch and internal observability tools.
• Document internal systems and operational processes to ensure maintainability and reproducibility.

Job Title

Data Robot Machine Learning Specialist

Relevant Experience

5 – 8 years (minimum 2 years hands-on with Data Robot Auto ML platform)

Location

Remote / Hybrid (Preferred: Chennai, India)

Type of Hire

Open to Persons with Disabilities (PwD) and Non-PwD candidates

Availability

Immediate joiners preferred

Role Summary

We are looking for a results-oriented Machine Learning professional with deep expertise in Data Robot to build, deploy, and monitor high-impact ML models across diverse business domains. You will own the end-to-end modeling lifecycle—from data preparation and project setup in DataRobot through production deployment and performance tracking—while guiding stakeholders on best practices for responsible AI.

Must-Have Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, or related field
• 2+ years direct experience with DataRobot (v7+)—AutoPilot, Feature Discovery, MLOps, and APIs
• Strong Python or R skills for custom modeling and data wrangling
• Solid grasp of supervised & unsupervised algorithms, evaluation metrics, and model interpretability techniques
• Hands-on SQL; familiarity with data warehouses (Snowflake, BigQuery, Redshift, etc.)
• Experience deploying models via REST endpoints or message queues (Kafka, RabbitMQ)
• Comfort presenting technical results to business stakeholders

Dear All,

We are seeking a highly capable Machine Learning Engineer with deep expertise in fine-tuning Large Language Models (LLMs) and Vision-Language Models (VLMs) for intelligent document processing. This role requires strong knowledge of PEFT techniques (LoRA, QLoRA), quantization , transformer architectures , prompt engineering , and orchestration frameworks like LangChain . You’ll work on building and scaling end-to-end document processing workflows using both open-source and commercial models (OpenAI, Google, etc.), with an emphasis on performance, reliability, and observability.

• Fine-tune and optimize open-source and commercial LLMs/VLMs (e.g., LLaMA,Cohere, Gemini, GPT-4) for structured and unstructured document processing tasks.
• Apply advanced PEFT techniques (LoRA, QLoRA) and model quantization to enable efficient deployment and experimentation.
• Design LLM-based document intelligence pipelines for tasks like OCR extraction, entity recognition, key-value pairing, summarization, and layout understanding.
• Develop and manage prompting techniques (zero-shot, few-shot, chain-of-thought, self-consistency) tailored to document use-cases.
• Implement LangChain -based workflows integrating tools, agents, and vector stores for RAG-style processing.
• Monitor experiments and production models using Weights & Biases (W&B) or similar ML observability tools.
• Work with OpenAI (GPT series) , Google PaLM / Gemini , and other LLM/VLM APIs for hybrid system design.
• Collaborate with cross-functional teams to deliver scalable, production-ready ML systems and continuously improve model performance.
• Build reusable, well-documented code and maintain a high standard of reproducibility and traceability.

• Hands-on experience with transformer architectures and libraries like HuggingFace Transformers.
• Deep knowledge of fine-tuning strategies for large models, including LoRA , QLoRA , and other PEFT approaches.
• Experience in prompt engineering and developing advanced prompting strategies.
• Familiarity with LangChain , vector databases (e.g., FAISS, Pinecone), and tool/agent orchestration.
• Strong applied knowledge of OpenAI , Google (Gemini/PaLM) , and other foundational LLM/VLM APIs.
• Proficiency in model training, tracking, and monitoring using tools like Weights & Biases (W&B) .
• Solid understanding of deep learning , machine learning , natural language processing , and computer vision concepts.
• Experience working with document AI models (e.g., LayoutLM, Donut, Pix2Struct) and OCR tools (Tesseract, EasyOCR, etc.).
• Proficient in Python , PyTorch , and related ML tooling.

• Experience with multi-modal architectures for document + image/text processing.
• Knowledge of RAG systems , embedding models , and custom vector store integrations.
• Experience in deploying ML models via FastAPI , Triton , or similar frameworks.
• Contributions to open-source AI tools or model repositories.
• Exposure to MLOps , CI/CD pipelines , and data versioning.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

• Work on cutting-edge GenAI and Document AI use-cases.
• Collaborate in a fast-paced, research-driven environment.
• Flexible work arrangements and growth-focused culture.
• Opportunity to shape real-world applications of LLMs and VLMs.

Openings : Senior and Mid-Level

Location : Remote in India

Hours : IST

Rate: 25-35 LPA

Job Purpose

Analyzing, designing, developing and managing the data pipelines to release scalable Data Science models. The ML/Ops Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated and repeatable way.

Job Responsibilities

• Create and maintain a scalable code to deliver AI/ML processes.
• Design and implement the pipelines for building and deployment of ML models.
• Design dashboards to monitor a system.
• Collect metrics and create alerts based on them.
• Design and execute performance tests.
• Perform feasibility studies/analysis with a critical point of view.
• Support and maintain (troubleshoot issues with data and applications).
• Develop technical documentation for applications, including diagrams and manuals.
• Working on many different software challenges always and ensuring a combination of simplicity and
• maintainability within the code.
• Contribute to architectural designs of large complexity and size, potentially involving several distinct
• software components.
• Work as a member of a team, encouraging team building, motivation and cultivating effective team
• relations.

Required Experience

• Demonstrated experience and knowledge in Linux and Docker containers
• Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS)
• Proficient in programming languages: Python
• Experience with ML/Ops technologies like Azure ML
• Experience with SQL
• Experience in the use of collaborative developing tools such as Git, Confluence, Jira, etc.
• Strong ability to analyze and synthesize. (Good analytical and logical thinking capability)
• Proactive attitude, resolutive, used to work in a team and manage deadlines.
• Ability to learn quickly
• Agile methodologies development (SCRUM/KANBAN).
• Minimal work experience of 6 years with evidence.
• Ability to keep fluid communication written and oral in English, both written and spoken

Preferred Experience

• Demonstrated experience and knowledge in unit and integration testing
• Experience or Exposure with AI/ML frameworks: PyTorch, Onnx, Tensorflow
• Experience designing and implementing CICD pipelines for automation.
• Experience designing monitoring dashboards (Grafana or similar)