1069 Llm Jobs - Page 31

What you will do In this vital role you will work closely with Amgen Research partners and Technology peers to ensure that they technology/ data needs for drug discovery research are translated into technical requirements for solution implementation. The role demonstrates scientific domain and business process expertise to detail product requirements as epics and user stories, along with supporting artifacts like business process maps, use cases, and test plans for the software development teams. Function as a Scientific Business Systems Analyst within a Scaled Agile Framework (SAFe) product team Serve as a liaison between global Research Informatics functional areas and global research scientists, prioritizing their needs and expectations Manage a suite of custom internal platforms, commercial off-the-shelf (COTS) software, and systems integrations Lead the Large Molecule Discovery technology ecosystem and ensure that the platform meets the requirements for data analysis and data integrity Ensure scientific data operations are scoped into building Research-wide Artificial Intelligence/Machine Learning capabilities Ensure operational excellence, cybersecurity and compliance. What we expect of you We are all different, yet we all use our unique contributions to serve patients. The delivery team to estimate, plan, and commit to delivery with high confidence and identify test cases and scenarios to ensure the quality and performance of IT Systems. Basic Qualifications: Masters degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Bachelors degree with 6- 8years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field Preferred Qualifications: 5+ years of experience in implementing and supporting biopharma scientific software platforms. Functional Skills: Must-Have Skills: Proven expertise in a scientific domain area and related technology needs Experience with writing user requirements and acceptance criteria in agile project management systems such as JIRA Experience in configuration and administration of LIMS/ELN platforms (e.g. Benchling), Discovery software tools (e.g. Geneious, Genedata Screener) and Instrument Automation and Analysis platforms Experience using platforms such as Spotfire, Tableau, Power BI, etc., to build dashboards and reports and understanding of basic data querying using SQL, Databricks, etc. Good-to-Have Skills: Experience leading the implementation of scientific software platforms, Electronic Lab Notebook (ELN), or Laboratory Information Management Systems (LIMS) Knowledge of the antibody discovery design, make, test, and analyze cycle. Experience in AI and machine learning for drug discovery research and preclinical development Experience with leveraging LLM tools to accelerate software development processes. Experience with cloud (e.g. AWS) and on-premise infrastructure.

Notice - Immediate - 15 days serving. PF Mandatory! Role & responsibilities 5+ years of experience in machine learning, with a focus on generative models or autonomous agents. Proficiency in Python and ML frameworks such as PyTorch Experience with LLMs (e.g., GPT, Claude, LLaMA, Cortex), transformers, and diffusion models. Familiarity with agent frameworks (e.g., LangChain, AutoGPT, ReAct, OpenAgents). Experience with AWS and Snowflake services Prior Healthcare experience Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems. Excellent problem-solving and communication skills. -- Thanks & Regards, Karthik Kumar, IT Recruiter SP Software (P) Limited (An ISO, ISMS & CMMI Level-3 Certified company) An SP Group Enterprise. Connect on : linkedin.com/in/b-karthik-kumar-116990179

We are seeking a talented Java backend Software Engineer with expertise in software engineering to join our team. As a Full Stack Software Engineer, your primary responsibility will be to develop & integrate Generative AI solutions that focus on technology improvements. Specifically, you will be working on projects involving Generative AI solutions for Technology Assistants & Data Management Efficiencies and will contribute for Java backend development such as IDE plugins Data Connections & Integrators. Responsibilities : - Collaborate with cross-functional teams such as Data Scientists, Product Partners and Partner Team Developers to identify opportunities for process improvements that can be solved using machine learning and generative AI. - Write clean, high-performance, high-quality, maintainable code. - Create connectors to various Content and Collaboration tools using tool specific API's such as Jira, Slack, Git etc - Create backend applications using Java, docker & in-house frameworks to orchestrate AI applications - Design and develop Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions. - Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs. - Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications. Requirements: - A Master's or Ph.D. degree in Computer Science or a related field. - Proven experience working as a Software Engineer, with a focus on Java, and exposure to Generative AI Applications such as chatGPT. - Strong proficiency in programming languages such as Java, Kotlin, Scala etc ( Mandatory) - Experience or Exposure in creating IDE Plugins for PyCharm, VS Code, IntelliJ & Web Consoles ( Nice to have ) - Experience in python and data pipelines ( nice to have) - Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies. - Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Nice to have ) - Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders. - Proven ability to adapt and learn new technologies and frameworks quickly. - A proactive mindset with a passion for continuous learning and research. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Job description AI/ML Model Development: Design, develop, deploy machine learning models to solve real-world problems Utilize frameworks such as TensorFlow, PyTorch, or similar to build scalable AI/ML solutions. Implement model training, validation, deployment Required Candidate profile Large Language Model (LLM) Integration Develop integrate Large Language Models (LLMs), including those by OpenAI, into existing new apps F ine-tune pre-trained LLMs to meet specific business needs

Job description AI/ML Model Development: Design, develop, deploy machine learning models to solve real-world problems Utilize frameworks such as TensorFlow, PyTorch, or similar to build scalable AI/ML solutions. Implement model training, validation, deployment Required Candidate profile Large Language Model (LLM) Integration Develop integrate Large Language Models (LLMs), including those by OpenAI, into existing new apps F ine-tune pre-trained LLMs to meet specific business needs

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Should lead key initiatives in GenAI COE on new tech trends, R and D on new product POC Work on proposals, Provide solutions architecture design solution on different business use cases Ability to work across various different GenAI Models and cloud providers Should have a strong experience in implementing projects in Digital Engineering Or Data Analytics Technically lead a team of developers and groom talent Extensive implementation experience in data analytics space or a senior developer role in one of the modern technology stack Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java Ability to build API based scalable solutions and debug & troubleshoot software or design issues Hands on exposure to integrating atleast one of the popular LLMs(Open AI GPT, PaLM 2, Dolly, Claude 2, Cohere etc.) using API endpoints. Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support Hands on exposure to using cloud(Azure/GCP/AWS) services for storage, serverless-logic, search, transcription and chat Extensive experience with data engineering and should be hands on in using Agentic AI Framework, RAG

Experience: 4+ years of experience in AI and machine learning Expertise in Python: Demonstrable experience with Python, including its data science and AI libraries such as TensorFlow, PyTorch, spaCy, and GPT (OpenAI). Familiarity with other programming languages such as Java or C++ is a plus. Azure OpenAI and Cloud Services: Hands-on experience with Azure OpenAI services, and a good understanding of other Azure services such as Azure Machine Learning, Azure Functions, and Azure Logic Apps for integrating AI capabilities. LLM and NLP Techniques: Deep understanding of Natural Language Processing (NLP) techniques, including tokenization, sentiment analysis, entity recognition, and especially the mechanics and applications of Large Language Models (LLMs). Creative Prompt Design: Ability to craft and refine prompts that effectively guide LLMs in producing desired textual outputs. This includes understanding different prompt types, such as zero-shot, few-shot, and chain-of-thought prompting. Strong programming skills in Python and familiarity with AI development tools and libraries. Should have hands-on experience in deploying at least one end to end GenAI project Knowledge of AI model training, fine-tuning, and deployment processes Excellent problem-solving and analytical skills Effective communication and interpersonal skills Qualification We are seeking skilled LLM Engineers with 5 to 8 years of experience to design, fine-tune, and implement large language model (LLM)-based solutions for an AI integration project. This role involves developing AI-driven functionalities tailored for Salesforce CRM and service ticketing platforms using Azure OpenAI and OpenAI technologies. Key Responsibilities: Develop and deploy LLM-based solutions for AI integration into Salesforce and service ticketing systems. Fine-tune pre-trained language models (e.g., GPT) to align with business requirements and enhance application performance. Collaborate with architects and stakeholders to implement generative AI-driven solutions for workflow automation and customer support. Ensure optimized performance and accuracy of LLMs for use cases such as ticket categorization, routing, and customer interaction. Design and implement scalable, secure, and compliant LLM-based architectures. Stay updated on advancements in AI/ML and LLM technologies and apply innovative techniques to solve business challenges. Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or related fields. 5 to 8 years of experience in software development or machine learning, with strong exposure to LLMs and generative AI models. Hands-on experience with Azure OpenAI, OpenAI APIs (e.g., GPT models), and their integration into enterprise systems. Proficiency in programming languages such as Python, with a focus on NLP libraries and ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Strong understanding of data preprocessing, model training, and optimization techniques for large-scale applications. Preferred Skills: Experience integrating LLM-based solutions with Salesforce and service ticketing platforms. Knowledge of cloud deployment and automation practices using tools like Docker, Kubernetes, or Azure DevOps. Familiarity with API development and integration for real-time AI functionalities. Understanding of data governance, security, and compliance standards in AI implementations

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

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

Job Summary We are seeking a highly skilled Generative AI Data Scientist to design, develop, and deploy generative AI applications and models that can generate meaningful insights, creative business domain content, or solve domain-specific challenges. The ideal candidate will combine expertise in data science, machine learning, AI and natural language processing (NLP) with a passion for innovation and real-world applications. As part of the EXL Digital AI R&D Innovation team, you will work as a Data Scientist in the Innovation unit supporting all EXL Business Units. You will be exposed to hundreds of different enterprise GenAI business use cases and help our clients create value architecting GenAI applications and solutions. This role involves working on cutting-edge Generative AI technologies to drive significant revenue growth, operational efficiencies, and enhanced customer experiences for our Fortune 1000 enterprise clients across various industries in insurance, healthcare, banking & financial services, media, and retail. You will work with a team of talented data scientists, AI researchers, software engineers, ML engineers, project managers and delivery managers helping them in deploying advanced AI technologies. Youll work with domain-specific data, design models and AI systems & architectures at scale, design RAG pipelines, improve AI Governance and responsible, LLM selection(GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) & fine-tuning PEFT LoRa/QLoRa adapters, LLM Prompt Engineering, Agentic AI, AutoGen, AI Autonomous Agents, Multimodal LLMs and LLM orchestration architectures for enterprise data at scale in Python. Key Responsibilities Model Development: Research, design, and develop state-of-the-art generative models such as GPT, GANs, VAEs, or diffusion models for tasks like text generation, summarization, reasoning, Q&A, or predictive analytics. Fine-Tuning: Fine-tune pre-trained models (e.g., Llama3, Mistral, OpenAI GPT, BERT, T5) to meet domain-specific requirements. Data Preparation: Clean, preprocess, and structure large datasets to train, validate, and test generative AI models. Deployment: Implement scalable solutions for deploying generative AI models in production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). Collaboration: Work closely with cross-functional teams, including product managers, engineers, and stakeholders, to align AI solutions with business goals. Evaluation: Develop metrics and benchmarks to evaluate model performance and ensure quality outputs. Research: Stay up to date with the latest advancements in AI/ML, particularly in generative AI techniques, and propose innovative solutions. Ethical AI Practices: Ensure ethical considerations are addressed in model development, including fairness, accountability, and explainability. Experience of architecting AI systems to solve complex business problems. Build advanced RAG pipelines, text chunking, and retrieval, LLM Prompt Engineering, using Vector Databases. Implement right LLM selection based on use cases and client criteria (GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) while managing trifecta of accuracy, cost, and latency/scale. Develop, fine-tune, context tune and implement state-of-the-art NLP models including Large Language Models like GPT, Llama3.1, Claude, BLOOM, Flan-T5, Falcon etc. fine-tuning PEFT LoRa/QLoRa adapters design AI systems & architectures, while considering good Responsible AI standards and AI Governance. Build Agentic AI, AutoGen, Muti-agents use cases, AI Autonomous Agents and LLM orchestration architectures for enterprise data at scale in Python. Hands on experience with complementary technologies around LLMs like embedders, vector databases (chroma, weaviate etc.), orchestration tools like Langchain, LlamaIndex etc. Conduct research and experimentation to improve existing models and propose novel approaches. Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications. Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities. Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications. Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices. Qualifications Education and Experience: Masters of Science or PhD in computer science, data science, statistics, Natural Language Processing 2-3 years of experience in GenAI and Large Language Models. Strong programming skills in Python, including experience with libraries like TensorFlow, PyTorch, Hugging Face Transformers, or similar. as evidenced by released code (e.g., GitHub repositories – version control awareness). Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning. Hands-on experience with generative AI models, such as Llama3, GPT4, Claude Knowledge of NLP, computer vision, or multimodal AI techniques. Proficiency in data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Experience in Generative AI Models and LLMs, finetuning LLMs, prompt engineering and experience with LLM orchestration frameworks like Langchain, LlamaIndex, RAGAS, etc. Strong software engineering skills for rapid and accurate development of AI models and systems. Understanding of Agentic AI, Autonomous Agents, AI Agents, AutoGen, Crew.ai, Langchain, and workflow steps design. NVIDIA Blueprints. Google AI Agents. Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders. Experience working in a collaborative environment, contributing to multidisciplinary teams and projects. Proven ability to solve complex problems, think creatively, and adapt to evolving research trends. Experience in deploying ML models in cloud environments (AWS SageMaker, GCP AI Platform, or Azure ML). Strong problem-solving and analytical skills. Excellent communication skills, both technical and non-technical. Skills and Competencies: 5 years of experience in AI, NLP including transformer architecture and LLMs, Computer Vision and related technologies Excellent communication and problem-solving skills. Working with cross-functional teams across different stakeholders. Ability to explain GenAI to non-technical audiences across many different industries. Ability to do GenAI Architecture solutioning for existing clients and potential clients. People leadership skills. Candidate is also hands on developer while people managing Data Scientists, ML Engineers etc. Experience in ML Engineering and MLOps, MLFlow Strong understanding of statistical and machine learning concepts Experience with deep learning frameworks such as TensorFlow and PyTorch Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models. Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow. Understanding of Graph Database and/or Vector Database along with knowledge of cloud services (e.g., AWS, Azure, GCP). Experience with deploying AI models in production environments. Familiarity with domain-specific applications of generative AI Leveraged both Azure and AWS for model inferencing. For finetuning, he has worked more on AWS SageMaker. Has used different retrieval, reranking, and generation techniques based on the use case complexity and the metrics required. Has played multiple roles in the past, such as an individual contributor, a solution architect, a mentor, a trainer, and a people manager. He also participates in RFI, RFP, thought leadership, and business development activities. ole & responsibilities Preferred candidate profile Perks and benefits

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.