1047 Llm Jobs - Page 21

Use GPT API or Llama to develop custom frameworks for investment management alternate data analysis Use Orchestration tools like N8n for document ingestion Setup on cloud or private using Coreweave Lead Machine Learning and UI Engineers Required Candidate profile 3+ years of development experience in .NET , Python and Azure 3+ years of experience in Data Science along with hands on GenAI and LLMs Experience with VectorDB, documentation ingestion workflows etc.

1.Design and Development of APIs: Create robust, scalable APIs to interface with large language models (LLMs). Develop endpoints for sending and receiving data from the LLM, ensuring that requests (e.g., text prompts) and responses are efficiently processed and communicated between the front end and back end. 2.Request and Response Handling: Implement systems that properly structure user inputs (e.g., transforming data into LLM-readable formats) and format the model outputs to meet application needs. Design logic to handle various types of responses, including error handling, fallback mechanisms, and retries. 3.Middleware and Pre/Post-Processing: Develop middleware to preprocess inputs before sending them to the LLM (e.g., tokenization, language translation, or contextual enhancements). Post-process responses to improve output readability, filter inappropriate content, or integrate additional functionality, such as summarization or answer extraction. 4.Performance Optimization: Focus on reducing latency in API calls to provide fast responses, especially for real-time applications. Implement strategies such as request batching, caching, and efficient data flow management to minimize delays and maximize throughput. 5.Security and Authentication: Set up secure API access with authentication mechanisms such as API keys, OAuth, or token-based access. Implement rate limiting, request logging, and auditing to prevent abuse and monitor usage. 6.API Versioning and Maintenance: Manage versioning to ensure backward compatibility when updates or changes to the LLM or API occur. Document and implement updates without disrupting existing users, ensuring smooth transitions for new versions. 7.Cost and Usage Optimization: Implement systems that minimize unnecessary API calls to control costs associated with using LLMs. Build mechanisms to track usage, set cost thresholds, and develop strategies like response caching to reduce API call frequency. 9.Collaboration with Other Teams: Work closely with machine learning engineers to ensure the LLMs API integration is seamless. Collaborate with frontend developers to ensure that the LLMs responses fit the applications user interface and experience. Location: Chennai/Noida/Pune/Trichy

Location: Hyderabad, India | Employment Type: Full-Time Experience Level: 2+Years Company: Covasant Contact Person: Ranjith Reddy 9703455109 | ranjith.palle@covasant.cm | linkedin.com/in/ranjith-r-75a766227 Build the Future of AI with Covasant At Covasant , we don't just work with AI we engineer the next era of it. We're hiring mid-level to senior developers and AI leads to help us build next-generation agentic AI systems that are intelligent, collaborative, and scalable. This is your chance to go beyond prompt engineering and shape the architecture of autonomous, multi-agent AI solutions using tools like LangGraph, AutoGen, CrewAI , and more. If youve got the skills and curiosity to work on what the AI world will be talking about next year , we want to hear from you. Your Role Design and develop multi-agent LLM systems using LangGraph, AutoGen, or CrewAI. Build and deploy MCP servers , LLM gateways , and design Agent-to-Agent collaboration flows. Fine-tune language models for verticals like healthcare, manufacturing, or finance. Architect retrieval-augmented generation (RAG) systems with vector stores like FAISS, Pinecone, or Weaviate. Integrate tools like LangSmith , GuardrailsAI , and knowledge graphs to ensure trust, safety, and observability. Collaborate cross-functionally with product, data science, and engineering teams. What You Bring 2+ years in software development, with strong Python skills. Proven expertise in one or more: LangGraph , AutoGen , CrewAI . Deep understanding of Agent-based AI , LLM orchestration , and RAG pipelines . Experience fine-tuning LLMs and applying prompt engineering and domain adaptation . Familiarity with tools like LangSmith , PromptGuard , or Guardrails frameworks. Bonus If You Have Cloud experience (AWS, Azure, GCP) Familiarity with Docker, Kubernetes Exposure to multi-modal models (LLaMA, Mistral, Falcon) Frontend tech: React, Angular, or Vue CI/CD, MLOps, or LLMOps knowledge Important We’re currently hiring mid-level, senior, and lead professionals with hands-on experience in AI/ML projects . These openings are not for freshers or professionals with less than 2 years of experience — but we are planning something exciting for early-career AI talent soon! Why Join Covasant Work on real-world agentic AI systems ahead of industry trends Collaborative and innovation-first work culture Competitive pay, benefits & performance incentives Hybrid/flexible work setup A chance to lead and influence the next chapter in AI Let’s Connect If this excites you — whether or not you're actively job hunting — don’t miss the chance to explore this game-changing opportunity. Ranjith Reddy – 9703455109 ranjith.palle@covasant.cm Connect with me on LinkedIn – I’d love to stay in touch, even if this isn’t the right time. Apply now or just start a conversation. The future of AI doesn’t wait — and neither should you.

Location: Remote Timings: Full Time (As per company timings) Notice Period: (Immediate Joiner - Only) Experience: 4 Years Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Job Overview We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher. The drive to make a positive impact on customers' lives.

Job Overview We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher. The drive to make a positive impact on customers' lives.

Senior Data Scientist Gen AI Experience: 3 - 6 Years Exp. Salary : INR 25-33 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 10:00AM to 7:00PM IST Opportunity Type: Onsite (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Gen AI Good to have skills : MDM platforms Blend360 (One of Uplers' Clients) is Looking for: Senior Data Scientist Gen AI who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description We are hiring a Senior Data Scientist (Generative AI) to spearhead the development of advanced AI-powered classification and matching systems on Databricks. You will contribute to flagship programs like the Diageo AI POC by building RAG pipelines, deploying agentic AI workflows, and scaling LLM-based solutions for high-precision entity matching and MDM modernization. Key Responsibilities Design and implement end-to-end AI pipelines for product classification, fuzzy matching, and deduplication using LLMs, RAG, and Databricks-native workflows. Develop scalable, reproducible AI solutions within Databricks notebooks and job clusters, leveraging Delta Lake, MLflow, and Unity Catalog. Engineer Retrieval-Augmented Generation (RAG) workflows using vector search and integrate with Python-based matching logic. Build agent-based automation pipelines (rule-driven + GenAI agents) for anomaly detection, compliance validation, and harmonization logic. Implement explainability, audit trails, and governance-first AI workflows aligned with enterprise-grade MDM needs. Collaborate with data engineers, BI teams, and product owners to integrate GenAI outputs into downstream systems. Contribute to modular system design and documentation for long-term scalability and maintainability. Qualifications Bachelors/Masters in Computer Science, Artificial Intelligence, or related field. 5+ years of overall Data Science experience with 2+ years in Generative AI / LLM-based applications. Deep experience with Databricks ecosystem: Delta Lake, MLflow, DBFS, Databricks Jobs & Workflows. Strong Python and PySpark skills with ability to build scalable data pipelines and AI workflows in Databricks. Experience with LLMs (e.g., OpenAI, LLaMA, Mistral) and frameworks like LangChain or LlamaIndex. Working knowledge of vector databases (e.g., FAISS, Chroma) and prompt engineering for classification/retrieval. Exposure to MDM platforms (e.g., Stibo STEP) and familiarity with data harmonization challenges. Experience with explainability frameworks (e.g., SHAP, LIME) and AI audit tooling. Preferred Skills Knowledge of agentic AI architectures and multi-agent orchestration. Familiarity with Azure Data Hub and enterprise data ingestion frameworks. Understanding of data governance, lineage, and regulatory compliance in AI systems. Interview Process Online Assessment Technical Screenings -2 Technical Interviews - 2 Project Review Client Interview How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. The company has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace. About Uplers: Uplers is the #1 hiring platform for SaaS companies, designed to help you hire top product and engineering talent quickly and efficiently. Our end-to-end AI-powered platform combines artificial intelligence with human expertise to connect you with the best engineering talent from India. With over 1M deeply vetted professionals, Uplers streamlines the hiring process, reducing lengthy screening times and ensuring you find the perfect fit. Companies like GitLab, Twilio, TripAdvisor, and AirBnB trust Uplers to scale their tech and digital teams effectively and cost-efficiently. Experience a simpler, faster, and more reliable hiring process with Uplers today.

Lead Python Developer Experience: 6 - 9 Years Exp. Salary : INR 30-36 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 10:00AM to 7:00PM IST Opportunity Type: Onsite (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Docker, Python, Gen AI Good to have skills : LLM Blend360 (One of Uplers' Clients) is Looking for: Lead Python Developer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description We are seeking a highly skilled Senior Python Engineer with extensive experience in FastAPI and microservices architecture to join our dynamic team. The ideal candidate will have a strong technical background, proven leadership in technical teams, and expertise in building scalable, resilient, and secure applications. Key Responsibilities : Lead the design, development, and deployment of applications using microservice architecture. Develop and maintain FastAPI-based backend services with high performance and scalability. ¢ Implement best practices in logging, monitoring, health checks, scalability, resilience, service discovery, API gateways, and error handling. ¢ Ensure code quality, security, and performance optimization. ¢ Work with containerization technologies like Docker and Kubernetes for application deployment. ¢ Collaborate with cross-functional teams to define, design, and ship new features. ¢ Establish and manage CI/CD pipelines for seamless application deployment. ¢ Implement best practices for API design, development, and security. ¢ Set up and maintain monitoring and logging tools (e.g., Prometheus, Grafana). ¢ Ensure adherence to version control systems (e.g., Git) and collaborative workflows. Qualifications : ¢ Proven experience in leading technical teams and developing applications using microservice architecture. ¢ Strong proficiency in Python and FastAPI. ¢ Deep understanding of Pydantic for data validation in FastAPI. ¢ Experience with containerization (Docker, Kubernetes). ¢ Familiarity with CI/CD pipelines and automation tools. ¢ Knowledge of API design and implementation best practices. ¢ Experience working with monitoring and logging tools (e.g., Prometheus, Grafana). ¢ Strong understanding of security best practices in microservices-based applications. Nice to Have : ¢ Experience with Retriever models, including implementation of chunking strategies. ¢ Familiarity with vector databases and their use cases. ¢ Understanding of optimal approaches in querying LLM models via API. ¢ Experience with prompt engineering and different strategies for effective interactions with LLMs. ¢ Exposure to various prompt engineering techniques in different scenarios Interview Process Online Assessment Technical Screenings -2 Technical Interviews - 2 Project Review Client Interview How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. The company has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace. About Uplers: Uplers is the #1 hiring platform for SaaS companies, designed to help you hire top product and engineering talent quickly and efficiently. Our end-to-end AI-powered platform combines artificial intelligence with human expertise to connect you with the best engineering talent from India. With over 1M deeply vetted professionals, Uplers streamlines the hiring process, reducing lengthy screening times and ensuring you find the perfect fit. Companies like GitLab, Twilio, TripAdvisor, and AirBnB trust Uplers to scale their tech and digital teams effectively and cost-efficiently. Experience a simpler, faster, and more reliable hiring process with Uplers today.

Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. Experience with SQL, Excel, Tableau/ Power BI, PowerPoint Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) Experience applying various machine learning techniques and understanding the key parameters that affect their performance Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs Excellent verbal and written communication Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: Connect with internal / external POC to understand the business requirements Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis Create project plan and sprints for milestones / deliverables Spin VM, create and optimize clusters for Data Science workflows Create data pipelines to ingest data effectively Assure the quality of data with proactive checks and resolve the gaps Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms Research whether similar solutions have been already developed before building ML models Create optimized data models to query relevant data efficiently Run relevant ML / DL algorithms for business goal seek Optimize and validate these ML / DL models to scale Create light applications, simulators, and scenario builders to help business consume the end outputs Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively Integrate and operationalize the models in client ecosystem Document project artifacts and log failures and exceptions. Measure, articulate impact of DS projects on business metrics and finetune the workflow based on

We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.Qualifications2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers. Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred. Excellent software engineering and programming skills, especially Python and SQL. A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher. The drive to make a positive impact on customers' lives.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Key Responsibilities: Build Scale AI ProductsDevelop and scale AI-driven B2C products with >1L MAU. Model ExpertiseWork withclosed models(OpenAI, Vertex AI)open-source LLMs(Llama, DeepSeek). Real-World AI ApplicationsFine-tune ground LLMs for domain-specific knowledge. Retrieval Function CallingImplement information retrieval and function-calling mechanisms. Evaluation FrameworksDesign long-term evaluation frameworks for AI performance improvements. What We re Looking For: 3-4 years of startup experiencewith managerial capability to build lead teams. Proven AI expertise, with a strong track record in applied AI LLMs. B2C Product SuccessBuilt and scaled AI-powered products with significant user adoption (>1L MAU). Hands-on experiencein AI frameworks, model tuning, and real-world LLM applications.

Job Role: Kore.AI & LLM Integration Specialist Job Location: Chennai, Pune Experience Slab 6-10 years. Domain --Telecom Mandatory Skills: Kore.AI platform experience LLM (Large Language Model) integration and implementation expertise Required Qualifications: Hands-on experience with Kore.AI , including bot development, NLP configuration, and integrations. Strong working knowledge of LLM models , such as GPT, Claude, or similar including fine-tuning, prompt engineering, and use in conversational AI workflows. Proficiency in Java and Spring Boot is a plus. Familiarity with AWS services (e.g., Lambda, S3, API Gateway, Bedrock, SageMaker) is a plus.

1.2–4 years of experience in data science and machine learning using Python. 2.Strong knowledge of libraries like NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch. 3.Hands-on experience with LLMs, NLP tasks, and fine-tuning/pretraining models. Required Candidate profile 1.Familiarity with AI/ML deployment and performance tuning. 2.Experience working with REST APIs, JSON, and integration of ML models into applications.

We are seeking a highly skilled and innovative Data Scientist with a strong focus on Generative AI, NLP, and Large Language Models (LLMs). The ideal candidate will design, develop, and deploy end-to-end data science solutions that harness the power of advanced ML, deep learning, and Gen AI technologies to drive real-world impact. Key Responsibilities: Design and implement scalable data science solutions using Generative AI, NLP, and ML techniques. Develop, fine-tune, and evaluate Large Language Models (LLMs) such as GPT, BERT, and similar architectures. Analyze structured and unstructured data to generate actionable insights for business problems. Collaborate cross-functionally with engineering, product, and business teams to integrate AI models into production systems. Conduct cutting-edge research in Gen AI and deep learning; evaluate and apply recent advancements. Build and maintain robust pipelines for model training, evaluation, monitoring, and deployment. Communicate complex technical findings clearly to technical and non-technical stakeholders. Required Skills & Qualifications: Strong hands-on experience with Generative AI, LLMs (e.g., OpenAI, Hugging Face Transformers, etc.). Proven expertise in core NLP tasks: text classification, summarization, named entity recognition, sentiment analysis, etc. Proficient in Python and related libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch. Experience developing, validating, and deploying ML models in production environments. Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings, and semantic search. Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps tools/workflows (CI/CD, model monitoring, etc.). Preferred Qualifications: Experience in prompt engineering, Retrieval-Augmented Generation (RAG), or fine-tuning/customizing LLMs. Contributions to AI research papers, open-source projects, or participation in ML competitions (e.g., Kaggle) is a plus. Knowledge of responsible AI practices, model interpretability, and bias mitigation techniques.

candidates with experience in Agentic AI frameworks (e.g., LangChain, AutoGPT, Semantic Kernel), LLM who are passionate about product development and AI/ML Engineering.

Role: Sr. Data Scientist - Data Scientist Relevant Experience: 7 Years Key Responsibilities - Bachelor's or Master's Degree in Computer Science, IT Engineering, or related fields. Overall 8+ years and Minimum of 2+ years of experience in delivering AI-powered products, with at least 2 years of dedicated Product Management experience. At least 1 years of experience with GPT/ LLM model development, including pre-processing, feature selection, and hyper-parameter tuning Experience working on Agentic AI solutioning , Develop and train GPT/LLM models to generate natural language text for various applications such as chatbots, question-answering systems, and recommendation engines. Hands on Experience in Graph RAG and agentic AI Hands on experience on Autogen and copilot agents Collaborate with cross-functional teams to define product requirements and develop use cases for GPT/LLM models. Conduct data analysis, pre-processing, feature engineering and model selection to create accurate models in a timely and efficient manner. Continuously monitor the accuracy and performance of the models, and iterate to improve the model's performance based on feedback. Strong analytical, strategic thinking, leadership, problem-solving, and project management skills. Exceptional attention to detail, combined with the ability to think innovatively and address challenges at both macro and micro levels.Defining the vision for the Data / AI use with senior leaders for the medium and long term. Share, update and align the vision of the use cases with senior stakeholders to act as the clear guide path for adoption and growth.

Role : Data scientist Exp : 5 - 8 Years Location : Pune,Chennai Notice period:30 Days Key Skill /Skill Specialization Data Scientist Mandatory Skills Data Scientist with expertise in Classic ML, Computer Vision, Deep Learning, and Large Language Models (LLMs), Python Desired Skills Exposure to GIT, GitHub actions, NPM, Yarn, Knowledge of Cloud will be a plus Knowledge of data pipelines Exposure to Postgres Prior exp of Oil & Gas Exp of working in Agile project" Job Description : "The ideal candidate will be passionate about solving complex problems and driving innovation through advanced AI techniques. 1. Develop and Deploy ML Models: - Implement and deploy machine learning models, including regression, classification, and clustering algorithms. - Design and train models to provide actionable insights from large datasets. 2. Integrate Advanced Technologies: - Enhance product offerings by integrating Computer Vision techniques such as image processing, convolutional neural networks (CNNs), and object detection. - Apply Deep Learning methodologies, including neural networks, recurrent neural networks (RNNs), and generative adversarial networks (GANs). - Experiment with Large Language Models (LLMs) for natural language processing tasks, utilizing transformer-based models like BERT, GPT, and T5. 3. Collaborate with Cross-Functional Teams: - Work closely with product managers, engineers, and domain experts to translate business requirements into technical solutions. - Participate in brainstorming sessions and contribute to the ideation of new AI-driven features. 4. Mentorship and Knowledge Sharing: - Guide and mentor junior data scientists, fostering a culture of continuous learning and knowledge exchange. Need to work in challenging agile model. Should have very good communication skills Experience of working in Agile based projects" Interested candidates can share their updated CV to pravallika@wrootsglobal.in

Job Title: AI/ML Engineer Python Backend & LLMs Job Summary: We are seeking a Python Backend Engineer with experience in AI/ML workflows , particularly LLMs and LangChain . The role focuses on developing Generative AI-driven applications, integrating LLMs, building data-pipelines, and backend services. Prior experience with generative AI is strongly preferred. Key Responsibilities: Implement LangChain/LangGraph workflows for AI-driven automation. Fine-tune LLMs for business applications. Build and optimize FastAPI-based backend services. Manage data pipelines and storage using PostgreSQL . Deploy and scale AI models using Docker (Kubernetes is a plus). Work with AWS SageMaker, GCP Vertex AI, or Azure ML for model deployment. Improve inference efficiency and reduce latency for real-time AI applications. Required Skills: Strong Python backend development (FastAPI preferred). Experience with LLMs, and prompt engineering . Hands-on experience with LangChain/LangGraph . Knowledge of PostgreSQL and scalable data storage. Familiarity with Docker, Kubernetes for containerization. Exposure to at least one cloud platform (AWS/GCP/Azure).

Location: Remote Timings: Full Time (As per company timings) Notice Period: (Immediate Joiner - Only) Experience: 4 Years Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Responsibilities : - Navigate and modify complex Rust codebases using CLI tools like grep and ripgrep. - Implement new features with a focus on memory safety, ownership rules, and type correctness. - Write and execute tests using cargo test, including property-based testing (proptest or quickcheck). - Refactor existing Rust code while maintaining functionality and performance. - Debug and fix memory safety, ownership, and concurrency-related issues. - Set up and manage Rust development environments using cargo, including handling dependencies and feature flags. - Ensure best practices in Rust development, including proper error handling, concurrency safety, and efficient memory usage. Requirements : - Strong experience with Rust programming language concepts, including ownership, borrowing, and lifetimes. - Familiarity with Rust frameworks like Tokio, Actix, Rocket and libraries such as Serde and Rayon. - Experience with Rust's testing ecosystem, including unit, integration, and property-based testing. - Knowledge of multi-threading and asynchronous programming in Rust. - Ability to work with complex architectural patterns and refactor code without introducing regressions. - Strong debugging skills, including fixing memory and concurrency issues. - Experience with performance profiling and benchmarking in Rust (cargo bench). - 4+ years of work experience This role provides an opportunity to work on challenging Rust engineering problems while improving AI-assisted programming workflows. If you're passionate about Rust and eager to push the boundaries of AI-driven software development, we'd love to hear from you! Nice to Have : - Experience contributing to open-source Rust projects. - Familiarity with writing Rust documentation and designing APIs with doc-tests. - Search Guidance Mandatory Skills : Rust - 3 yrs, Rust Frameworks(Tokio, Actix, Rocket) - 3 yrs, Libraries(Serde and Rayon) - 3 years Nice To Have : Rust documentation and designing APIs with doc-tests. Total Years Of exp : 5+ years experience Overlap Required : 4 hours Pst

About Role : A NASDAQ-listed company that has effectively maintained its position as the front-runner technology sector, is looking to onboard a skilled Python developer keen is helping them expand the power of AI in the mobile coding ecosystem with the ultimate goal of creating new assisting AI-powered tools for the development domain. The company is developing the next generation of coding assisting agents, which will have a wide range of uses. For those who are keen to learn in a fast-paced setting, this is an exciting opportunity. Responsibilities : - Navigate and modify complex Rust codebases using CLI tools like grep and ripgrep. - Implement new features with a focus on memory safety, ownership rules, and type correctness. - Write and execute tests using cargo test, including property-based testing (proptest or quickcheck). - Refactor existing Rust code while maintaining functionality and performance. - Debug and fix memory safety, ownership, and concurrency-related issues. - Set up and manage Rust development environments using cargo, including handling dependencies and feature flags. - Ensure best practices in Rust development, including proper error handling, concurrency safety, and efficient memory usage. Requirements : - Strong experience with Rust programming language concepts, including ownership, borrowing, and lifetimes. - Familiarity with Rust frameworks like Tokio, Actix, Rocket and libraries such as Serde and Rayon. - Experience with Rust's testing ecosystem, including unit, integration, and property-based testing. - Knowledge of multi-threading and asynchronous programming in Rust. - Ability to work with complex architectural patterns and refactor code without introducing regressions. - Strong debugging skills, including fixing memory and concurrency issues. - Experience with performance profiling and benchmarking in Rust (cargo bench). - 4+ years of work experience This role provides an opportunity to work on challenging Rust engineering problems while improving AI-assisted programming workflows. If you're passionate about Rust and eager to push the boundaries of AI-driven software development, we'd love to hear from you! Nice to Have : - Experience contributing to open-source Rust projects. - Familiarity with writing Rust documentation and designing APIs with doc-tests. - Search Guidance Mandatory Skills : Rust - 3 yrs, Rust Frameworks(Tokio, Actix, Rocket) - 3 yrs, Libraries(Serde and Rayon) - 3 years Nice To Have : Rust documentation and designing APIs with doc-tests.