569 Llm Jobs

Our client INFOSYS is looking for Artificial Intelligence Engineer position with 5+ years of experience in Pune location. CONTRACT TO HIRE AND WORK FROM OFFICE Job Description : Mandatory Skills : Python + LLMs + AI + Azure Certified. ole Definition: This is a specialized role for an AI Software Engineers design, build, and deploy scalable AI models and systems. They work with machine learning frameworks, cloud platforms, and data engineering tools to create and optimize AI solutions. Skills: Proficient: Languages/Framework: Fast API, Azure UI Search API (React) Cloud: Azure Cloud Basics (Azure DevOps) Gitlab: Gitlab Pipeline Ansible and REX: Rex Deployment Data Science: Prompt Engineering + Modern Testing Data pipeline development Understanding of AI/ML algorithms and their applications MLOps frameworks Knowledge of cloud platforms (Azure ML especially) Model deployment process o Data pipeline monitoring Expert: (in addition to proficient skills) o Languages/Framework: Azure Open AI o Data Science: Open AI GPT Family of models 4o/4/3, Embeddings + Vector Search o Databases and ETL: Azure Storage Account, Postgresql, Cosmos o Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) o Knowledge of cloud platforms (AWS SageMaker, Google AI Platform) o Expertise in data preprocessing, feature engineering, and model evaluation o Understanding of software engineering principles (version control, CI/CD, containerization) o Familiarity with distributed computing and big data tools (Spark, Hadoop) o Ability to optimize models for performance and scalability o Experience with Azure AI Search

Position Overview We are hiring five AI Engineers with 12 years of experience to join our dynamic team in Hyderabad. The ideal candidates will have a solid foundation in Large Language Models (LLMs) , LangChain , and Generative AI (GenAI) frameworks. This is a great opportunity to work on innovative AI solutions, contributing to projects that integrate LLMs , prompt engineering , RAG pipelines , and cloud-based deployments . Key Responsibilities Contribute to the design and development of AI-powered applications utilizing LLMs (GPT-3.5, GPT-4, Gemini). Assist in building LangChain-based pipelines and workflows, including LangSmith and LangGraph . Support the implementation of Retrieval-Augmented Generation (RAG) frameworks using vector databases such as ChromaDB . Apply prompt engineering techniques to optimize model responses and improve contextual accuracy. Develop RESTful APIs using Flask or FastAPI to enable model consumption in production environments. Write and manage data workflows using SQL , PySpark , and Spark SQL . Deploy and monitor models on Azure Machine Learning or AWS Bedrock platforms. Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. Required Skills Proficiency in Python , SQL , PySpark , and Spark SQL Hands-on experience with LLMs : GPT-3.5, GPT-4, Gemini Knowledge of LangChain , LangSmith , LangGraph Familiarity with Vector Databases (e.g., ChromaDB) and embeddings Experience with prompt engineering and RAG-based architectures Exposure to cloud platforms such as Azure ML or AWS Bedrock Strong understanding of REST APIs and version control systems (Git/GitHub) Preferred Qualifications Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field Internship or academic project experience in NLP, LLMs, or GenAI technologies Familiarity with MLOps tools and practices (e.g., CI/CD, Airflow) Strong problem-solving abilities, attention to detail, and a collaborative mindset

What You'll Do We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will build core agent infrastructureA2A orchestration and MCP-driven tool discoveryso teams can launch secure, scalable agent workflows. You will be reporting to Senior Manager, Machine Learning What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Promote innovation by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards, contributing to the project's. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful 6+ years of experience building Machine Learning models and deploying them in production environments as part of creating solutions to complex customer problems. Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. Experience working with technological innovations in AI & ML(esp. GenAI) and apply them. Experience with design patterns and data structures. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, Agents, A2A, MCP, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, and Grafana.

3+yrs mandatory into Software Development 1+yrs mandatory exp. with LLMs & AI Frameworks Strong in Python & AI frameworks LLM Orchestration (LangChain) Understanding of Vector Databases

About the Role: We are seeking a highly skilled and motivated Senior Data Scientist with 56 years of experience to drive the development of intelligent AI systems. This role requires extensive hands-on experience with Large Language Models (LLMs) , strong background in Agentic AI , Machine Learning , and Python programming . You will work on designing autonomous agents, building scalable ML pipelines, and integrating advanced LLM-powered solutions into real-world products. Key Responsibilities: Architect and implement agentic AI systems that use LLMs for autonomous reasoning, planning, and multi-step task execution. Lead the development, fine-tuning, evaluation, and deployment of Large Language Models (LLMs) using frameworks like Hugging Face Transformers, LangChain, LLM orchestration tools, and vector databases. Develop ML models using supervised, unsupervised, and reinforcement learning techniques, and integrate them into production environments. Design and build end-to-end machine learning pipelines, including data ingestion, feature engineering, training, and deployment. Optimize model performance and latency in real-world applications and implement model monitoring and retraining strategies. Collaborate with cross-functional teams including product, engineering, and business to translate AI capabilities into product features. Mentor junior data scientists and contribute to the team's technical excellence and innovation. Required Skills & Experience: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search.Understanding of multi-agent collaboration, goal decomposition, and planning architectures. les, autonomous agents, and task orchestration. Experience with cloud platforms (AWS, GCP, or Azure) and scalable infrastructure for deploying AI models. Exposure to API development, ML model serving, and integration with real-time systems. Excellent communication and collaboration skills in cross-functional environments. Educational Qualification: Bachelor of Technology (B.Tech) in Computer Science, Data Science, Artificial Intelligence, or a related field from a recognized institution. Preferred Qualifications: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search. Understanding of multi-agent collaboration, goal decomposition, and planning architectures.

Hi Immediate opening for Data Scientist Lead Location : Ahmedabad ( Onsite only ) Experience : 6 + years Job Description : Key Skills : Advanced degree or Masters degree in machine learning/data science/computer science or a related field Proven experience in developing and deploying machine learning models in a healthcare or RCM setting Strong programming skills in languages like Python or R Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Deep understanding of healthcare data and industry-specific challenges Strong problem-solving and analytical abilities Excellent leadership and team management skills Effective communication and stakeholder management skills Experience in MLOps, containerization, CI/CD pipeline is a plus Role & responsibilities: Engage with business and product teams to identify and flesh out ML use-cases Responsible for identifying needs, ingestion, quality and value evaluation, distillation & analysis of both structured and unstructured data from multiple sources Researching solutions to overcome machine learning challenges Managing and mentoring a team of ML engineers work allocation and planning, problem solving, tactical problem solving and thought leadership Leading development and optimization of machine learning and deep learning models Customizing models and build on top of existing framework to address client specific requirements Creating assets to fast-track solution development Staying informed about latest developments in Data Science / AI field Candidates serving notice / Early Immediate joiners can share updated CV on anand.rawal@agshealth.com

Job Description: As an LLM Evaluation Expert specializing in Coding, you will play a crucial role in assessing and improving our language models' coding capabilities. Your expertise will be instrumental in evaluating LLM-generated code responses, making high-level judgments, and setting the standard for what constitutes excellent AI-assisted coding. Key Responsibilities: • Critically analyze and evaluate code responses generated by our LLMs across various programming languages and paradigms • Exercise expert judgment to select the most appropriate and efficient code solutions from multiple LLM-generated options • Make informed decisions on behalf of our customers, ensuring that selected code meets industry standards, best practices, and specific client needs • Develop and write coding demonstrations to illustrate "what good looks like" in AI-generated code, setting benchmarks for quality and efficiency • Provide detailed feedback and explanations for your evaluations, helping to refine and improve the LLM's understanding and output • Collaborate with the AI research team to identify areas for improvement in the LLM's coding capabilities • Stay abreast of the latest developments in software engineering, coding standards, and AI to ensure our evaluations remain cutting-edge Required Qualifications: • Advanced degree in Computer Science, Software Engineering, or a related field • Extensive experience (1+ years) in software development across multiple programming languages and paradigms • Demonstrated ability to critically evaluate code quality, efficiency, and adherence to best practices • Strong analytical and decision-making skills, with the ability to make complex judgments under ambiguous circumstances • Excellent written and verbal communication skills, with the ability to explain technical concepts clearly • Experience in technical writing, particularly in creating coding examples or tutorials Preferred Qualifications: • Previous experience working with or evaluating AI systems, particularly in the context of code generation • Familiarity with a wide range of software development methodologies and architectural patterns • Understanding of machine learning concepts, particularly as they apply to natural language processing and code generation • Experience in creating or contributing to coding standards or style guides This role requires a unique blend of technical expertise, critical thinking, and communication skills. You will be the bridge between advanced AI technology and practical, real-world coding applications. Your work will directly influence the development of next-generation AI coding assistants, shaping the future of software development. If you're passionate about code quality, have a keen eye for detail, and are excited about the potential of AI in software engineering, we encourage you to apply for this pivotal role at AGI Data Services.

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization . You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities 1) Technical Leadership Lead the technical design and architecture of complex Generative AI systems. Ensure solutions align with business objectives, scalability requirements, and technical feasibility. Guide development teams through best practices , architecture reviews, and technical decision-making processes. 2) Solution Architecture Design and develop end-to-end Generative AI solutions , including data pipelines , model training, deployment, and real-time monitoring. Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. Design, train, and fine-tune AI/ML models , especially Generative AI and Large Language Models (LLMs) , to address specific use cases. Build conversational AI solutions and chatbots using frameworks such as LangChain , RAG (Retrieval-Augmented Generation) , and Chain-of-Thought (COT) prompting . 3) Production Deployment Lead the deployment of Generative AI models into production environments . Optimize deployment pipelines leveraging tools like Docker, Kubernetes , and cloud-native services for orchestration. Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. 4) Data Processing & Feature Engineering Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. Implement data wrangling , preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Optimize workflows to extract meaningful insights from large datasets . 5) Model Optimization Identify and implement optimization strategies such as hyperparameter tuning , feature engineering , and model selection for performance enhancement. Focus on computational efficiency and scaling models to production-level performance. 6) Pilot/POCs Development Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. 7) Evangelization Promote and drive the adoption of Generative AI solutions across customer and delivery teams. Provide technical leadership and mentorship to teams working on GenAI projects. Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. 8) Continuous Improvement Stay at the forefront of AI advancements , frameworks, and tools, including emerging concepts in Generative AI. Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications 10+ years of experience in AI/ML architecture, model development, and production deployment Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions Hands-on experience with frameworks like LangChain , Retrieval-Augmented Generation (RAG) , and advanced prompting techniques Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting Experience working with cloud platforms , primarily GCP , with optional experience in AWS or Azure Strong understanding of MLOps tools, pipelines, and model monitoring in production Proficiency in Python and SQL for model development and data processing Experience with data preprocessing, ETL workflows , and feature engineering for AI applications Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions Experience working with large datasets for structured and unstructured AI applications Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies Proven track record of leading POCs/pilots and scaling them to production-grade deployments Preferred Skills Familiarity with Reinforcement Learning from Human Feedback (RLHF) . Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. Strong understanding of orchestration for large-scale production environments. Key Attributes Strong technical leadership and mentorship abilities. Excellent communication and stakeholder management skills. Strategic thinking with the ability to architect scalable and future-ready AI systems. Passion for solving business challenges using state-of-the-art AI techniques. Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us? Lead the development of cutting-edge Generative AI solutions for real-world applications. Be part of a collaborative, innovative, and technology-driven team. Opportunity to work with advanced AI/ML tools and frameworks. Drive innovation through technical leadership , mentorship, and solution evangelization. Continuous professional growth with access to the latest AI/ML technologies and frameworks.

Primary skill Gen AI developer Secondary skill Model hosting LLM knowledge. Ability to stay updated with the latest advancements in generative AI research and incorporate them into work. JD -Advanced programming knowledge, including mastery of programming languages such as Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. -Expertise in generative models such as generative adversarial networks (GANs) and variational autoencoders (VAEs). The candidate should be able to design, train, and optimize these models to generate high-quality, creative content. -Natural language processing (NLP) for text generation projects. This includes familiarity with techniques for text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. -Model hosting LLM knowledge -Ability to design and implement scalable and efficient AI systems. -Advanced knowledge of natural language processing for text generation tasks. -Familiarity with computer vision and image generation using AI. Akshay : Ignore -Skills in data preprocessing and feature engineering for AI model training. -Strong understanding of neural network architectures and optimization techniques.

Lead AI Engineer Job Description Educational Qualifications: Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Strong academic background with a focus on deep learning, natural language processing, and/or computer vision. Experience Requirements: 2+ years of experience in AI/ML research and development, with a proven track record of delivering innovative solutions. Extensive experience in working with and customizing Large Language Models (LLMs). Proficiency in popular AI development frameworks (e.g., TensorFlow, PyTorch, Keras). Strong programming skills in Python and/or other relevant languages. Experience in leading and mentoring AI/ML teams. Key Responsibilities: Lead the development and deployment of AI-powered solutions for the project. Interact with and customize LLMs to meet specific project requirements. Utilize popular AI development frameworks to build and optimize AI models. Collaborate with cross-functional teams (e.g., product, engineering, data science) to deliver AI solutions. Stay abreast of the latest advancements in AI/ML and incorporate them into the project. Desired Skills: Strong problem-solving and analytical skills. Excellent communication and interpersonal skills. Ability to work independently and as part of a team. Passion for AI and its potential to transform industries. Additional Considerations: Experience in cloud computing platforms (e.g., AWS, Azure, GCP) is a plus. Contributions to open-source AI/ML projects are highly valued. Publications in top-tier AI/ML conferences or journals are a plus. Note: This job description is intended to provide a general outline of the position's requirements. The specific responsibilities and qualifications may vary depending on the project and company needs.

About the role What you'll do Build and maintain backend systems that let AI agents interface with real services • Design and implement tool-calling pipelines, orchestrators, and external integrations • Work closely with clinical and product teams to define new agent capabilities • Contribute across the stack: APIs, infra, LLM workflows, internal tools Ready to shape the future of healthcare AI? .Help define engineering standards, observability, and system safety at scale • What we're looking for Engineering degree from a Tier 1 institute • 510 years of experience building and maintaining production-grade software • Proficiency in one or more backend languages (e.g. Python, Go, Java) • Solid understanding of databases, APIs, version control, and deployment practices • Comfort with ambiguity and a bias toward execution • Interest in applied AI and realworld problem-solving

Senior AI & ML Platform Engineer Location: Bengaluru Experience Level: 3 to 10 Years About the Role We are building next-generation AI-powered platforms that leverage Large Language Models (LLMs), advanced Machine Learning (ML), NLP, and agentic workflows to automate critical business processes across multiple domains. We are looking for experienced AI/ML Engineers who are passionate about building real-world AI productsnot just experimenting. You will help design, prototype, and deploy intelligent systems integrating LLMs, agents, APIs, and robust ML models for classification, prediction, and optimization. Responsibilities Build and integrate agentic AI workflows using LangChain or similar frameworks. Develop APIs and backend services to support LLM and ML-driven platforms. Implement, train, and optimize lightweight and scalable ML models for classification, prediction, and anomaly detection. Work with LLMs (OpenAI, Claude, Gemini) to fine-tune prompts, create retrieval-augmented generation (RAG) systems, and chain multi-step tasks. Design and optimize vector search implementations for LLM-driven applications. Integrate AI models with external systems (VMS platforms, ERP systems) using APIs. Implement document processing pipelines combining OCR with LLM/ML validation. Apply ML techniques for supply-demand forecasting, fraud detection, and optimization. Participate in design discussions, brainstorming sessions, and agile sprints. Collaborate with senior AI architects and SMEs to refine platform capabilities. Required Skills Strong experience in Python for ML and AI development. Expertise in ML frameworks such as TensorFlow, PyTorch, scikit-learn. Knowledge of NLP tasks (text extraction, classification, summarization). Experience building and optimizing RAG workflows with vector databases. Solid understanding of API development (FastAPI, Flask, or similar frameworks). Familiarity with prompt engineering and agent orchestration concepts. Ability to build scalable ML models for classification, forecasting, and anomaly detection. Experience integrating ML solutions with cloud services (AWS, Azure, GCP). Knowledge of OCR tools and techniques for document processing. Exposure to multi-agent architectures and reinforcement learning is a plus. Understanding of feature engineering, model evaluation, and optimization techniques. Mindset We Are Looking For Builders mindset: You love turning ideas into working solutions fast. Curiosity: Passionate about keeping up with the latest in GenAI and ML. Problem-solver: Comfortable working in ambiguous environments where solutions need discovery, not just execution. Collaboration: Open to learning from senior architects and iterating based on feedback.

Solix Technologies Inc. is a leading provider of big data applications for enterprise archiving, data privacy, and advanced analytics. We are on a mission to help organizations manage and leverage their data for maximum value, efficiency, and compliance. Job Summary: We are seeking a highly skilled and motivated Machine Learning Engineer with hands-on experience in Natural Language Processing (NLP) and Large Language Models (LLMs). You will play a key role in designing, developing, and deploying scalable ML/NLP solutions that drive intelligent automation and data insight across our platforms. Key Responsibilities: Design and develop machine learning models, particularly in the domain of NLP and LLMs. Fine-tune, evaluate, and deploy transformer-based models (e.g., BERT, GPT, T5, LLaMA, etc.). Apply techniques such as named entity recognition (NER), text classification, semantic search, summarization, and question answering. Work with large-scale datasets to extract insights and build data pipelines. Collaborate with cross-functional teams including data engineers, product managers, and software developers. Conduct experiments, model training, and optimization to improve accuracy and performance. Stay up-to-date with the latest research in NLP, LLMs, and machine learning. Required Skills and Experience: Bachelor's or Masters degree in Computer Science, Data Science, AI/ML, or a related field. Minimum 5+ years of hands-on experience with NLP and LLMs Proficient in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers. Strong understanding of modern NLP techniques (tokenization, embeddings, attention mechanisms, etc.). Experience with ML lifecycle including model development, evaluation, and deployment (MLOps). Familiarity with data handling libraries (Pandas, NumPy) and cloud platforms (AWS, GCP, or Azure). Good understanding of data preprocessing, feature engineering, and model validation techniques. Experience with open-source LLM fine-tuning and deployment. Knowledge of vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG). Prior experience with large-scale data systems or enterprise data environments. Published papers or open-source contributions in the ML/NLP space.

LLMs - OpenAI, Gemini, CoPilot etc. Good Knowledge of RAG Pipeline Architectures Fine/Prompt/Instruction Tuning of LLMs machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn). cloud services (GCP, Azure, AWS).

Leading a team of data scientists with roadmap and vision. Planning data projects. Building analytic systems and predictive models. Managing a team of data scientists, and machine learning engineers. Involve in pre-sales and building proposals. Apply strong expertise in machine-learning, deep learning, NLP, data mining, and information retrieval to design, prototype, and build the next-generation analytics engines and services Responsibilities Lead data mining and collection procedures Ensure data quality and integrity Interpret and analyze data problems Conceive, plan and prioritize data projects Build analytic systems and predictive models Test performance of data-driven products Visualize data and create reports Align data projects with organizational goal Understands business problems and designs end-to-end analytics use cases Develops complex models and algorithms that drive innovation throughout the organization. This may include improving on-time performance, network planning, etc., Conducts advanced statistical analysis to provide actionable insights, identify trends, and measure performance Collaborates with model developers to implement and deploy scalable solutions Provides thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders Qualification & Other Attributes: 8-15 years experience in a statistical and/or data science role Proven experience as a Data Scientist or similar role Strong organizational and leadership skills Degree in Computer Science, Data Science, Mathematics, or similar field Deep knowledge and experience in Large Language Models (LLM) Strong knowledge on Generative AI Deep knowledge of machine learning, statistics, optimization or related field Experience in Linear and non-Linear Regression models including Multiple and Multivariate Experience in Classification models including Ensemble techniques Experience in Unsupervised models including K-Means, DBSCAN, LOF Rich Experience in NLP techniques Experience in Deep Learning techniques like CNN, RNN, GAN, Markov etc (Any 3 or 4) Strong real-time experience with atleast one of the machine language softwares like R, Python, Matlab is mandatory Good knowledge in Explainable AI Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) Excellent written and verbal communication skills along with strong desire to work in cross functional teams Attitude to thrive in a fun, fast-paced start-up like environment Additional advantage of having experience in semi, unstructured databases like MongoDB, Cassandra, ArangoDB, Couchbase, GraphDB, etc Optional: programming in C, C++, Java, .Net

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Do Instrumental in understanding the requirements and design of the product/ software Develop software solutions by studying information needs, studying systems flow, data usage and work processes Investigating problem areas followed by the software development life cycle Facilitate root cause analysis of the system issues and problem statement Identify ideas to improve system performance and impact availability Analyze client requirements and convert requirements to feasible design Collaborate with functional teams or systems analysts who carry out the detailed investigation into software requirements Conferring with project managers to obtain information on software capabilities Perform coding and ensure optimal software/ module development Determine operational feasibility by evaluating analysis, problem definition, requirements, software development and proposed software Develop and automate processes for software validation by setting up and designing test cases/scenarios/usage cases, and executing these cases Modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. Analyzing information to recommend and plan the installation of new systems or modifications of an existing system Ensuring that code is error free or has no bugs and test failure Preparing reports on programming project specifications, activities and status Ensure all the codes are raised as per the norm defined for project / program / account with clear description and replication patterns Compile timely, comprehensive and accurate documentation and reports as requested Coordinating with the team on daily project status and progress and documenting it Providing feedback on usability and serviceability, trace the result to quality risk and report it to concerned stakeholders Status Reporting and Customer Focus on an ongoing basis with respect to project and its execution Capturing all the requirements and clarifications from the client for better quality work Taking feedback on the regular basis to ensure smooth and on time delivery Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team members. Consulting with engineering staff to evaluate software-hardware interfaces and develop specifications and performance requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code Documenting very necessary details and reports in a formal way for proper understanding of software from client proposal to implementation Ensure good quality of interaction with customer w.r.t. e-mail content, fault report tracking, voice calls, business etiquette etc Timely Response to customer requests and no instances of complaints either internally or externally Stakeholder Interaction Stakeholder Type Stakeholder Identification Purpose of Interaction Internal Lead Software Developer and Project Manager Regular reporting & updates Software Developers For work coordination and support in providing testing solutions External Clients Provide apt solutions and support as per the requirement Display Lists the competencies required to perform this role effectively: Functional Competencies/ Skill Leveraging Technology Knowledge of current and upcoming technology along with expertise in programming (automation, tools and systems) to build efficiencies and effectiveness in own function/ Client organization Competent Process Excellence - Ability to follow the standards and norms to produce consistent results, provide effective control and reduction of risk Expert Technical knowledge knowledge of various programming languages, tools, quality management standards and processes - Expert Competency Levels Foundation Knowledgeable about the competency requirements. Demonstrates (in parts) frequently with minimal support and guidance. Competent Consistently demonstrates the full range of the competency without guidance. Extends the competency to difficult and unknown situations as well. Expert Applies the competency in all situations and is serves as a guide to others as well. Master Coaches others and builds organizational capability in the competency area. Serves as a key resource for that competency and is recognised within the entire organization. Behavioral Competencies Formulation & Prioritization Innovation Managing Complexity Execution Excellence Passion for Results Deliver / No. / Performance Parameter / Measure - 1. Continuous Integration, Deployment & Monitoring of Software 100% error free on boarding & implementation, throughput %, Adherence to the schedule/ release plan 2. Quality & CSAT On-Time Delivery, Manage software, Troubleshoot queries Customer experience, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: Python, GenAI, AWS Preferred Skills: NLP , AI/ML , LLM Architect and implement Al solutions utilizing cutting-edge technologies like LLM, Langchain, and Machine Learning. AIML solution development in Azure using Python Ability to build and finetune the model to improve the performance Create own technology if off-the-shelf technology is not solving the problem. E.g changes to traditional RAG approaches, finetune LLM, create architectures. Use experience and advise leadership and team of data scientists best approaches, architectures for complex ML use cases. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Create end to end AI systems with responsible AI principles Develop data pipelines using SQL to extract and transform data from Snowflake for Al model training and inference. Possess expertise in Natural Language Processing (NLP) & GenAI to integrate text-based data sources into the Al architecture. Collaborate with data scientists and engineers to ensure seamless integration of Al components into existing systems. Responsible for continuous communication about the team progress to keystakeholder.

Azure DevOps Engineer with 5–7 yrs exp to manage CI/CD, IaC, AKS, LangChain, FastAPI, Redis, PostgreSQL, Angular in Azure. Strong in Terraform, monitoring, and AI integration. Immediate joiners only.

Role & responsibilities Minimum Qualifications: • 23 years of hands-on experience developing production-grade LLM applications. • 3 to 5 years of overall software development experience. • Minimum 1 year of experience in autonomous agent development using the LangGraph framework or similar. Must-Have Skills: 1. Production-Grade LLM Development: Proven experience in developing and deploying large language model applications. 2. Autonomous Agent Development: Hands-on experience with frameworks like LangGraph for building autonomous agents. 3. Advanced RAG Architectures: Expertise in hybrid search, multi-vector retrieval, and contextual compression. 4. Prompt Engineering and Vector Search Optimization: Proficiency in crafting effective prompts and optimizing vector searches. 5. Performance Tuning and Token Optimization: Strong understanding of response caching and techniques to optimize token usage. Nice-to-Have Skills: 1. Scalable Architectures: Experience with Kubernetes, Docker, and cloud platforms, preferably Azure. 2. NoSQL Databases: Familiarity with MongoDB and ElasticSearch. 3. API-Driven Development: Knowledge of building and maintaining APIs. 4. CI/CD Pipelines and Agile Methodologies: Experience with continuous integration/continuous deployment pipelines and Agile practices. 5. Analytical and Problem-Solving Skills: Strong analytical abilities

Dear candidate, We found your profile suitable for our current opening, please go through the below JD for better understanding of the role, Job Description : Role : Lead Data Scientist / TA Exp : 12 - 20 years Mode of work : Hybrid Model (3daya WFO) Work Location : Hyderabad/Bangalore/Noida/Pune/Kolkata Job Description: We are looking for a highly experienced Lead Data Scientist / ML Engineer to drive innovation in Generative AI (GenAI) , search technologies , recommendation engines , and agentic AI systems . This role demands both technical excellence and strategic vision, combining deep hands-on expertise in AI/ML with proven leadership in building and scaling data science teams. Key Responsibilities: 1. Technical & Strategic Leadership Define and execute AI strategies aligned with business goals. Lead and mentor a high-performing team of data scientists and ML engineers. Drive architectural decisions and innovation in AI-powered products. 2. Generative & Agentic AI Build and deploy GenAI models for text generation and content automation. Develop agentic AI systems with autonomous task planning and decision-making capabilities. Apply latest deep learning advancements (transformers, diffusion models, etc.) to real-world use cases. 3. Search & Recommendation Systems Design scalable, high-performance search and recommendation platforms. Implement ML models for ranking, personalization, and relevance optimization. Leverage real-time feedback loops and experimentation (A/B testing). 4. Large Language Models (LLMs) Fine-tune and operationalize LLMs (e.g., GPT, BERT) for NLP tasks. Work closely with product teams to integrate LLMs into applications. Establish best practices for LLMOps, including prompt engineering and monitoring. 5. Machine Learning Engineering & MLOps Build robust ML pipelines for model development, deployment, and monitoring. Implement MLOps using CI/CD, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure). Ensure responsible AI practices and data governance compliance. 6. Collaboration & Stakeholder Engagement Translate business needs into ML solutions in partnership with product and engineering teams. Communicate insights and recommendations to stakeholders across levels. Promote a culture of data-driven decision-making. 7. Research & Innovation Stay updated on the latest in AI/ML and contribute to R&D efforts. Encourage experimentation, POCs, and technical publications. Required Qualifications: Masters or PhD in Computer Science, AI, Data Science, or related field. 12+ years of experience in data science/ML, with 5+ years in leadership roles. Strong experience in: Generative AI (e.g., GANs, VAEs, transformer models) Search & Recommendation Systems LLMs & NLP using frameworks like Hugging Face, TensorFlow, PyTorch Agentic AI and autonomous systems ML Engineering & MLOps Leadership skills with proven success in managing cross-functional teams. Strong communication and stakeholder management abilities. Preferred Skills: Experience with big data tools (Spark, Hadoop, Kafka). DevOps tools: Jenkins, GitLab CI, Terraform. Exposure to edge computing and distributed systems. Contributions to open-source AI/ML projects or research publications. Please check below link for organisation details https://www.tavant.com/ If interested , please drop your resume to dasari.gowri@tavant.com Regards Dasari Krishna Gowri Associate Manager - HR www.tavant.com

We are looking for a skilled AI Engineer with 3 to 8 years of experience in software engineering or machine learning to design, implement, and productionize LLM-powered agents that solve real-world enterprise problems. This position is based in Kolkata. Roles and Responsibility Architect and build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark and iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Job Requirements Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go is a bonus. Hands-on experience with at least one LLM/agent framework and platform (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar).

Company Name - Fission Labs Apply Here - https://app.fabrichq.ai/jobs/0e46cebe-8b91-4a96-9061-950b66dc4d54 About Us: Headquartered in Sunnyvale, with offices in Dallas & Hyderabad, Fission Labs is a leading software development company, specializing in crafting flexible, agile, and scalable solutions that propel businesses forward.With a comprehensive range of services, including product development, cloud engineering, big data analytics, QA, DevOps consulting, and AI/ML solutions, we empower clients to achieve sustainable digital transformation that aligns seamlessly with their business goals. Key Responsibilities Design and architect complex Generative AI solutions using AWS technologies Develop advanced AI architectures incorporating state-of-the-art GenAI technologies Create and implement Retrieval Augmented Generation (RAG) and GraphRAG solutions Architect scalable AI systems using AWS Bedrock and SageMaker Design and implement agentic AI systems with advanced reasoning capabilities Develop custom AI solutions leveraging vector databases and advanced machine learning techniques Evaluate and integrate emerging GenAI technologies and methodologies Technical Expertise Requirements Generative AI Technologies Expert-level understanding of: Retrieval Augmented Generation (RAG) Vector Database architectures Agentic AI design principles AWS AI Services Comprehensive expertise in: AWS Bedrock Amazon SageMaker AWS AI/ML services ecosystem Cloud-native AI solution design Technical Skills Advanced Python programming for AI/ML applications

Role: ML Engineer Experience: 3 to 15 Years Chennai location must or relocation also fine- Hybrid mode We have good budget Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

AI Engineer & Lead This role is a blend of technical innovation, strategic consulting, and hands-on problem-solving, making each day varied, challenging, and impactful. Exp: 3-8 Years Location: Chennai & Hyderabad Organization: Intellect Design Arena - Product Company ------------------------------------------------------------------------------------------------------------- About Intellect Design Arena Limited Intellect Design Arena Ltd is an enterprise-grade financial technology leader, providing composable and intelligent solutions for futuristic global financial institutions across 57 countries. Intellects revolutionary First Principles Thinking-based Enterprise Connected Intelligence Platform, eMACH.ai, is the most comprehensive, composable, and intelligent open finance platform in the world. With an impressive array of 329 microservices, 535 events, and over 1757 APIs, eMACH.ai enables financial institutions to design and deploy future-ready technology solutions that provide a significant global competitive edge. With three decades of domain expertise, Intellect offers a full spectrum of banking and insurance technology products through four lines of business: Global Consumer Banking (iGCB), Global Transaction Banking (iGTB), IntellectAI and Digital Technology for Commerce (iDTC). Intellect is a pioneer in applying Design Thinking and our 8012 FinTech Design Center, the world's first Design Center dedicated to Design Thinking Principles, underscores our commitment to continuous and impactful innovation, addressing the ever-growing need for digital transformation. We proudly serve over 325+ customers worldwide, supported by a diverse workforce of solution architects and domain and technology experts in major global financial hubs. Summary: As an AI Engineer, you will work directly with clients to own the implementation of AI solutions using our AI platform. You will build and deploy end-to-end AI workflows, taking projects from concept to production, and solving complex, real-world challenges at scale. Your insights and learnings from client engagements will directly contribute to the evolution of our platform, ensuring we stay at the forefront of AI innovation. You will play a key role in expanding our presence into new markets and problem spaces unlocked by Generative AI. Key Responsibilities: Deliver Production-Ready AI Solutions: Design and deploy AI Agents, data processing pipelines, that are robust, scalable, and suitable for real-world applications. Solve Real Business Problems: Focus on practical AI solutions that address tangible business challenges, moving beyond theoretical approaches. Collaborate Across Teams: Work effectively with both technical and non-technical stakeholders to ensure clear communication and smooth project execution. Adapt in Dynamic Environments: Operate comfortably in fast-paced, evolving settings, adjusting quickly to shifting objectives and direct user feedback. Drive Innovation and Growth: Embrace an entrepreneurial mindset, continuously learning, innovating, and striving to make a high impact in a rapidly changing field. Client Interaction and Strategy Development: Engage with clients to understand their challenges, develop AI strategies, and translate their needs into actionable technical solutions. Deploying Solutions to Production: Move AI workflows from prototype to production, ensuring they integrate smoothly into client environments and solve real-world problems. Iterating and Improving: Continuously enhance deployed solutions based on feedback and evolving requirements, focusing on debugging, performance improvement, and workflow adaptation. Contributing to Platform Evolution: Share field insights to influence the development of new features and capabilities within the AI platform, aligning it with market needs. Key Traits: Technical Proficiency: Expertise in building and deploying AI models, data pipelines, and advanced analytics in production environments. Problem-Solver: Ability to design practical, impactful AI solutions that address real business challenges, focusing on tangible outcomes Collaborative: Effective communication skills to work with diverse teams, including technical and non-technical stakeholders, and explain complex AI concepts in understandable terms. Adaptable: Comfortable working in dynamic, fast-paced environments with evolving objectives, quickly iterating on solutions based on feedback. Innovative and Entrepreneurial: Passion for continuous learning, innovation, and applying an entrepreneurial approach to drive impact and growth. Client-Focused: Strong ability to engage directly with clients, understand their needs, and align AI strategies with business objectives. Detail-Oriented: Focus on refining, testing, and fine-tuning AI solutions for optimal performance in real-world settings. Continuous Learner: Commitment to staying updated on the latest AI technologies, tools, and methodologies, exploring new approaches to keep skills and solutions cutting-edge. Skills and Qualifications: Proven experience developing solutions using Generative AI models, with a strong understanding of the AI landscape and related technologies. Solid foundation in Machine Learning principles, including evaluation, training, and problem decomposition. Strong background in engineering or a related technical field such as Computer Science, Mathematics, Software Engineering, Physics, or Machine Learning. Proficiency in programming languages such as Python, Java, C++, JavaScript/TypeScript, or similar. Interested folks can reach out to bicky.nath@intellectdesign.com

Experience: 10+ years overall | Minimum 10 full-cycle AI/ML project implementations, including GenAI experience Role Summary: We are seeking a AI Architect to lead strategic AI transformation initiatives within the retail domain. This role demands deep hands-on experience in AI, Machine Learning (ML), and Generative AI (GenAI), along with the ability to engage directly with C-level stakeholders, align technical delivery with business objectives, and drive enterprise-wide adoption of advanced AI solutions.The ideal candidate is a techno-strategic leader who can take AI/ML/GenAI projects from ideation to productionbuilding architectures, leading cross-functional teams, and ensuring regulatory and operational alignment in retail environments.Key Responsibilities:Consulting & Business Alignment Partner with senior business and IT leadership, including CIOs, CDOs, and COOs, to identify high-impact use cases across e-commerce, retail operations, supply chain, and customer experience. Translate complex retail challenges into technically feasible and scalable AI/ML/GenAI solutions. Create strategic roadmaps, capability assessments, and PoV/PoC execution plans that align with business KPIs and regulatory needs. Solution Architecture & Delivery Leadership Design and lead delivery of AI/ML/GenAI pipelines covering data ingestion, model training, validation, deployment, and monitoring. Build and scale GenAI-based solutions like LLM-driven chatbots, intelligent product recommendation engines, RAG pipelines, summarization tools, and virtual assistants. Architect cloud-native AI platforms using AWS (SageMaker, Bedrock), Azure (ML, OpenAI), or GCP (Vertex AI, BigQuery, LangChain). Define and implement MLOps and LLMOps frameworks for versioning, retraining, CI/CD, and production observability. Ensure adherence to Responsible AI principles, including explainability, bias mitigation, auditability, and compliance with retail regulations (GDPR, CCPA, SOC2, etc.). Engineering & Integration Work closely with data engineering teams to acquire, transform, and pipeline data from retail systems, customer databases, inventory management systems, and real-time feeds. Design architecture for data lakes, feature stores, and vector databases supporting AI and GenAI use cases. Enable seamless integration of AI capabilities into enterprise workflows, customer platforms, and decision engines via APIs and microservices. Required Skills & Experience: 10+ years of experience in AI/ML, data engineering, and cloud architecture. Minimum of 5 end-to-end AI/ML project implementations from use case discovery through to productionization. Proven expertise in: (Any One) AI/ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch GenAI/LLM platforms: OpenAI, Cohere, Mistral, LangChain, Hugging Face, vector DBs (Pinecone, FAISS, Chroma) Cloud platforms: AWS, Azure, GCP including AI/ML & GenAI native services MLOps/LLMOps tools: MLflow, Kubeflow, SageMaker Pipelines, Vertex AI Pipelines Strong experience with data security, governance, model risk management, and AI compliance frameworks relevant to retail. Ability to lead large cross-functional teams and engage both technical teams and senior stakeholders.

Role: Senior Backend Engineer. Exp:5 Years to 10 Years. Mode: Remote. Responsibilities Understand GenAI at a sufficient level of curiosity and usage (beyond simple applications such as using ChatGPT such as understanding and usage of Lang Chain, Lang Graph, Crew AI, OpenAI APIs etc. Be able to quickly understand our product hosted at https://app.galileo.ai/ Have 5 years of experience working on Product Engineering teams building service oriented or general micro services-based applications using Python Can work in a fast-paced environment and can get ideas quickly off the ground with minimal support (ideally has experience working in a mix of large enterprises and startup experience). Skill Requirements Programming languages: Python and Typescript Basic understanding of LLM (OpenAI/Gemini/) API and SDK Basic understanding of AI frameworks like Langchain, CrewAI etc. Has some exposure and understanding of Observability and Reliability (such as familiarity with OTEL, understanding of SLOs) Has some degree of familiarity with Cloud environments such as Azure, GCP and AWS If you are passionate about applying your experience in the AI/ML field to an emerging and advancing field of Generative AI, this is a great opportunity for you. You will get to work on a groundbreaking product poised to revolutionize the way companies approach LLM Evaluations. Join our team at Galileo and help us build the future of Evaluations in Generative AI.