1047 Llm Jobs - Page 18

Role & responsibilities We are looking for Gen AI Engineer permanent position with MNC company for Remote. Preferred candidate profile Senior Gen AI Engineer GenAI / ML (Python, Langchain) Full Time Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities We are looking for Senior Gen AI Engineer permanent position with MNC company for Remote. Preferred candidate profile Senior Gen AI Engineer GenAI / ML (Python, Langchain) Full Time Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Mirafra Technologies is Hiring #GenAIEngineer (#RAG, #LLM, #FineTuning) Are you passionate about Generative AI and cutting-edge technologies? Join We're looking for Gen AI Engineers with 3 to 5 years of experience in: Walk-In Date: Thursday, 3rd July 2025 Time: 11:00 AM 1:00 PM Job Location - #Bangalore and #Hyderabad Venue: Mirafra Technologies 2nd Floor, Akshay Tech Park, Plot No. 72 & 73, Vijayanagar, EPIP Zone, Whitefield, Bengaluru, Karnataka 560066 Contact Person: Vignesh D Requirements: 3 to 5yrs Strong experience with Gen AI frameworks Hands-on with LLM architecture and deployment Familiarity with RAG pipelines and fine-tuning techniques Solid programming skills in Python

Job Description The Role Project Manager, Collection Platforms and AI The Team Collection Platforms and AI team is responsible for driving key automation projects, AI/ machine learning based solutions, collection platforms and lean initiatives across Enterprise Data Organization. We are responsible for creating, planning, and delivering transformational projects for the company using state of the art technologies and data science methods, developed either in- house or in partnership with vendors. We are transforming the way we are collecting the essential intelligence our clients need to do decisions with conviction, delivering it faster and on a scale while maintaining the highest quality standards. The Impact This role will be a part of IT Product Management and will work in a team responsible for leading the project management side of strategic initiatives related to the area of Data Science, ML, Gen AI /LLM based solutions. The role involves creating and maintaining the momentum with stakeholders, focusing on value and incremental results while continuously looking for the latest and newest technologies and machine learning solutions available for various uses cases across the Market Intelligence Division. Whats in it for you: • You will be part of a team at the center of the transformation of a Fortune 500 company. • You will be spearheading the strategic projects, witnessing the whole project life cycle, and deploying the end-to-end machine learning based data extraction solution. • You will be working closely with stakeholders of various teams to understand their business challenges and to provide cutting–edge solutions to them. • You will be getting immense exposure to commercial discussion with the vendors and will actively participate in the discussion with Legal, Finance and Technology teams. • You will be part of a diverse, global and dynamic team. Responsibilities • Interpret project requirements analyze and develop project plans, , and lead an end-to-end execution of the project. • Engage with business leads and peers, interfaces with senior leaders across the organization. Builds strong internal and external relationships and ensures service quality and customer satisfaction

Mandatory Skills & Experience : - Expertise in designing and optimizing machine-learning operations, with a preference for LLM Ops.- Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting.- Experience on Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs. Contribute towards fine tune Transformer models for optimal performance in NLP tasks, if required. Implement and maintain automated testing and deployment processes for machine learning models w.r.t LLMOps. Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Develop and maintain robust monitoring and alerting systems for generative AI models ensuring proactive identification and resolution of issues. Research or engineering experience in deep learning with one or more of the following : generative models, segmentation, object detection, classification, model optimisations. Experience implementing RAG frameworks as part of available ready products. Experience in setting up the infrastructure for the latest technology such as Kubernetes, Serverless, Containers, Microservices etc. Experience in scripting/programming to automate deployments and testing, working on tools like Terraform and Ansible. Scripting languages like Python, bash, YAML etc. Experience on CI/CD opensource and enterprise tool sets such as Argo CD, and Jenkins (others like Jenkins X, Circle CI, Argo CD, Tekton, Travis, Concourse an advantage). Experience with the GitHub/DevOps Lifecycle. Experience in Observability solutions (Prometheus, EFK stacks, ELK stacks, Grafana, Dynatrace, AppDynamics). Experience in at least one of the clouds for example Azure/AWS/GCP. Significant experience on microservices based, container based or similar modern approaches of applications and workloads. You have exemplary verbal and written communication skills (English). Able to interact and influence at the highest level, you will be a confident presenter and speaker, able to command the respect of your audience. Desired Skills & Experience : Bachelor level technical degree or equivalent experience; Computer Science, Data Science, or Engineering background preferred; Master's Degree desired. Experience in LLM Ops or related areas, such as DevOps, data engineering, or ML infrastructure. Hands on experience in deploying and managing machine learning and large language model pipelines in cloud platforms (i.e., AWS, Azure) for ML workloads. Familiar with data science, machine learning, deep learning, and natural language processing concepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc. Experience in using retrieval augmented generation and prompt engineering techniques to improve the model's quality and diversity to improve operations efficiency. Proven experience in developing and fine tuning Language Models (LLMs). Stay up to date with the latest advancements in Generative AI, conduct research, and explore innovative techniques to improve model quality and efficiency. The perfect candidate will already be working within a System Integrator, Consulting or Enterprise organisation with 8+ years of experience in a technical role within the Cloud domain. Deep understanding of core practices including SRE, Agile, Scrum, XP and Domain Driven Design. Familiarity with the CNCF open source community. Enjoy working in a fast paced and dynamic environment using the latest technologies.

Manager Data Science Experience: 8-14 Years Exp Salary: 45 LPA to 50 LPA Preferred Notice Period : Within 30 Days Opportunity Type: Office (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills: Python, LLM, GenAI, Tensorflow, PyTorch, HuggingFace, NLP Blend360 (One of Uplers' Clients) is looking for: About Blend360: 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. Job Description We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models. Interview Process Step 1: Online Assessment Step 2: Technical Screenings 1: 1 Technical Screening with Technical Panel (45 mins) 1 Technical round with Senior Technical Panel (45 mins) Step 3: Technical Interviews 2 : 1 Technical rounds of Interview with Reporting Manager (45 mins) Agenda: To assess on technical parameters giving white board programming, problem solutioning and story telling 1 Technical rounds of Interview with Project Manager (45 mins) To assess on overall fitment Step 4: 1 Project Review (45 mins): 30 mins of presentation any chosen related topic with minimum 6 - 8 slides 10 - 15 mins Question and Answers by panels All interviewers will be part of the discussion. Step 5 : Client Interview (45 mins) How to apply for this opportunity: Easy 3 Step Process: 1. Click On Apply and register or log in to our portal 2.Upload updated Resume & complete the Screening Form 3. Increase your chances of getting shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Lead Data Science Experience: 5-8 Years Exp Salary: 35 LPA to 43 LPA Preferred Notice Period : Within 30 Days Opportunity Type: Office (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills: Python, LLM, GenAI, Tensorflow, Retrieval Augmented Generation(RAG) Blend360 (One of Uplers' Clients) is looking for: About Blend360: 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. Job Description We are hiring a Lead 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. 7+ 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 Step 1: Online Assessment Step 2: Technical Screenings 1: 1 Technical Screening with Technical Panel (45 mins) 1 Technical round with Senior Technical Panel (45 mins) Step 3: Technical Interviews 2 : 1 Technical rounds of Interview with Reporting Manager (45 mins) Agenda: To assess on technical parameters giving white board programming, problem solutioning and story telling 1 Technical rounds of Interview with Project Manager (45 mins) To assess on overall fitment Step 4: 1 Project Review (45 mins): 30 mins of presentation any chosen related topic with minimum 6 - 8 slides 10 - 15 mins Question and Answers by panels All interviewers will be part of the discussion. Step 5 : Client Interview (45 mins How to apply for this opportunity: Easy 3 Step Process: 1. Click On Apply and register or log in to our portal 2.Upload updated Resume & complete the Screening Form 3. Increase your chances of getting shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Role Summary We are seeking a skilled and hands-on Senior Artificial Intelligence & Machine Learning (AI/ML) Engineer to build and productionize AI solutionsincluding fine-tuning large language models (LLMs), implementing Retrieval-Augmented Generation (RAG) workflows, multi-agent applications and MLOps pipelines. This role focuses on individual technical contribution and requires close collaboration with solution architects, AIML leads, and fellow engineers to translate business use cases into scalable, secure, cloud-native AI services. The ideal candidate will bring deep technical expertise across the AI/ML lifecycle—from prototyping to deployment—while contributing to a culture of engineering excellence through peer reviews, documentation, and platform innovation. They will play a critical role in delivering robust, high-performance AI systems in partnership with the broader AI/ML team. Key Responsibilities Model Development & Optimization Fine-tune foundation models (e.g., GPT-4, Llama 3). Implement prompt engineering and basic parameter-efficient tuning (e.g., LoRA). Conduct model evaluation for quality, bias, and hallucination; analyze results and suggest improvements. RAG & Agentic Systems (Exposure, Not Ownership) Assist in building RAG pipelines: Participate in integrating and embedding generation, vector stores (e.g., FAISS, pgvector), and retrieval/ranking components. Work with multi-agent frameworks (e.g., LangChain, Crew AI) Production Engineering / MLOps Contribute to CI/CD pipelines for model training and deployment (e.g., GitHub Actions, SageMaker Pipelines). Help automate monitoring for latency, drift, and cost; assist in lineage tracking (e.g., MLflow). Containerize services with Docker and assist in orchestration (e.g., Kubernetes/EKS/GKE) Data & Feature Engineering Build and maintain data pipelines for collection, cleansing, and feature generation (e.g., Airflow, Spark). Implement basic data versioning and assist with synthetic data generation as needed Code Quality & Collaboration Participate in design and code reviews. Contribute to testing (unit, integration, guardrail/hallucination tests) and documentation. Share knowledge through sample notebooks and internal sessions Security, Compliance, Performance Follow secure coding and Responsible AI guidelines. Assist in optimizing inference throughput and cost (e.g., quantization, batching) under guidance. Ensure SLAs are met and contribute to system auditability Technology Stack Programming Languages & Frameworks Python (expert) JavaScript/Go/TypeScript (nice-to-have) Strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. PyTorch, TensorFlow/Keras, Hugging Face Transformers/PEFT, LangChain/LlamaIndex, Ray/PyTorch Lightning, FastAPI/Flask Experience working with RESTful APIs, authentication (OAuth, API keys), and pagination Cloud & DevOps Expertise in one or more cloud vendors like AWS, GCP, Azure Containers (Docker), Orchestration (Kubernetes, EKS/GKE/AKS) MLOps Databases Relational: PostgreSQL, MySQL NoSQL: MongoDB / DynamoDB Vector Stores: FAISS / pgvector / Pinecone / OpenSearch / Milvus / Weaviate RAG Components Document loaders/parsers, text splitters (recursive/semantic), embeddings (OpenAI, Cohere, Vertex AI), hybrid/BM25 retrievers, rerankers (Cross-Encoder) Multi-Agent Frameworks Crew AI / AutoGen / LangGraph / MetaGPT / Haystack Agents, planning & tool-use patterns Testing & Quality Unit/integration testing (pytest), guardrails Qualifications 7–10years total software/ML engineering experience, including 3+years delivering ML models or GenAI systems to production. Proven track record building and optimising RAG or LLMpowered applications at scale Proficiency in Python and ML frameworks (PyTorch, TensorFlow) and in cloudnative deployment (AWS/GCP/Azure). Handson experience with vector databases, embeddings, and prompt engineering. Experience in regulated industries (Fintech, Healthcare, eCommerce) is a plus. Experience with multiagent frameworks (CrewAI, AutoGen, LangGraph). Certifications such as AWS CertifiedMachineLearning Specialty / AzureAIEngineer / GoogleProfessionalMachineLearningEngineer. Bachelor’s degree in Computer Science, Data Science, Engineering or related discipline (Master’s preferred). Soft Skills & Leadership Attributes Ownership mindset: drives features from design through deployment and monitoring. Clear communicator: explains technical tradeoffs to stakeholders, writes concise docs, and updates project artefacts. Collaboration & mentorship: pairs with junior engineers, shares knowledge in brownbag sessions, gives constructive PR feedback. Continuous learning: tracks latest GenAI research, evaluates new tooling, and proposes incremental improvements.

GenAI Developer - 5+ years of Python development, Docker/Podman, API design, FastAPI, REST, and WebSocket integration.Experience with at least one LLM orchestration or agent framework (e.g.LangChain,AutoGen,OpenAgents) Mail:kowsalya.k2srsinfoway.com

Key Responsibilities: Develop, review, and refine domain-specific problems and solutions Evaluate AI outputs for accuracy, depth, and relevance across various subject areas Identify and correct conceptual, technical, or computational errors in AI-generated responses Collaborate in training and optimizing large language models using RLHF Required Qualifications: 1+ year of experience in a specific domain (Engineering, Sciences, Humanities, etc) Strong understanding of subject fundamentals and problem-solving approaches Ability to critically analyze and enhance AI-generated content

Key Responsibilities: Create, review, and refine Chemistry problems, solutions, and detailed explanations Evaluate AI-generated Chemistry content for scientific accuracy, clarity, and relevance Identify and correct errors in AI responses across various Chemistry topics Support training and fine-tuning of LLMs using RLHF methodologies Required Qualifications: 1+ year of experience in Chemistry-related domains (Teaching, Research, Content Development, etc) Strong knowledge in areas like Organic, Inorganic, and Physical Chemistry Ability to assess and enhance AI-generated responses critically Familiarity with academic or competitive exam content is a plus

Key Responsibilities: Create, review, and refine questions and answers related to core BBA subjects (Eg- Management, Marketing, HR, Business Law, Organizational Behavior) Analyze AI-generated responses for relevance, business accuracy, and clarity Identify and fix conceptual or factual inaccuracies in business-related AI content Contribute to training and fine-tuning LLMs using RLHF techniques Required Qualifications: 1+ year of experience in Business Administration-related domains (Teaching, Industry, Content Development, etc) Strong grasp of core BBA concepts including Marketing, HR, Strategic Management, and Business Communication Ability to critically evaluate AI-generated content and enhance quality Familiarity with academic, corporate, or case-based learning material is a plus

Role & Responsibilities: Help in the training of an AI assistant model to enhance its accuracy and performance Evaluate the model's responses across multiple dimensions to ensure quality and relevance Maintain high standards of speed and precision while assessing the model's responses Must Required Traits: Strong attention to detail Ability to carefully follow instructions Excellent proficiency in English

Key Responsibilities: Write clean, efficient Java code for AI model training and evaluation Debug and resolve issues in Java-based AI content or logic Evaluate and review AI-generated Java outputs for correctness and clarity Train and fine-tune LLMs using RLHF techniques Required Qualifications: 1+ year of experience in Java development, teaching, or related fields Strong understanding of core Java concepts like OOP, exception handling, file I/O, and collections Familiarity with Java frameworks and best practices Ability to critically assess and improve AI-generated Java code

Key Responsibilities: Write clean, efficient code for data processing and transformation Debug and resolve technical issues Evaluate and review code to ensure quality and compliance Training, fine-tuning the LLMs using RLHF techniques Required Qualifications: 1+ year of SQL development experience Expertise in writing complex SQL queries, optimizing database performance Designing database schemas Proficient in working with relational database management systems like MySQL, PostgreSQL, or SQL Server

Key Responsibilities: Create, review, and refine legal content including case studies, statutes, legal reasoning, and explanations Evaluate AI-generated responses for legal accuracy, clarity, and logical consistency Identify and correct errors in legal interpretation or application by AI models Assist in training LLMs using RLHF to improve understanding of legal language and frameworks Required Qualifications: 1+ year of experience in Law (Academia, Practice, Legal Writing, etc ) Strong understanding of core legal concepts (Constitutional Law, Contract Law, Criminal Law, etc ) Familiarity with case law analysis, legal citation standards, and jurisprudence Ability to critically review AI responses for legal validity

Overview: TekWissen is a global workforce management provider throughout India and many other countries in the world. The below clientis a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place one that benefits lives, communities and the planet Job Title: Software Engineer Senior Location: Chennai Work Type: Onsite Position Description: As a Software Engineer on our team, you will be instrumental in developing and maintaining key features for our applications. You'll be involved in all stages of the software development lifecycle, from design and implementation to testing and deployment. Skills Required: Python, GCP Cloud Run, Big Query, CI/CD, Angular, GCP, Java Skills Preferred: LLM Experience Required: Bachelor's degree in computer science, Engineering, or a related field. 5+ years of professional software development experience. Strong proficiency in JavaScript, HTML, and CSS. Solid experience with Angular frameworks. Experience designing and developing RESTful APIs. Experience with Backend Technologies-Node.js, Python, Java. Experience with Data Engineering tools- Big Query, Terraform, Tekton, Data Flow, Data Proc, Astronomer/Air Flow etc. Experience with GCP App Engine, Cloud Functions, Kubernetes. Proficient with Git version control. Experience with testing frameworks (e.g., Jest, Mocha, Jasmine). Understanding of software development best practices and design patterns. Experience with cloud-native CI/CD pipelines. Experience with integrating Large Language Models (LLMs) into applications. Contributions to open-source projects. Experience with other cloud platforms (e.g., AWS, Azure). Familiarity with DevOps principles and practices. Education Required: Bachelor's Degree TekWissen Group is an equal opportunity employer supporting workforce diversity.

Core Responsibilities Design and implement machine learning models, including Generative AI and Large Language Models (LLMs), to solve complex business problems. Integrate AI/ML solutions, including open-source LLMs (Llama, Falcon, Mistral, etc.), with existing Node.js applications. Process, clean, and transform data for model training and inference. Optimize model performance, fine-tune LLMs, and improve deployment pipelines. Collaborate with cross-functional teams, partners, and stakeholders to develop AI-driven solutions. Apply AI and ML research, including Generative AI, to enhance software development and business workflows. Develop and maintain RESTful APIs for seamless interaction with ML models and LLM-based applications. Required Technical Skills Generative AI & LLMs Experience with open-source LLMs (e.g., Llama, Falcon, Mistral) and fine-tuning techniques. Machine Learning & AI – Hands-on experience with frameworks like TensorFlow, PyTorch, and scikit-learn Data Processing – Strong expertise in data manipulation using pandas, NumPy, and other relevant tools. Model Deployment – Knowledge of model serving techniques in JavaScript environments for real-world applications. Node.js Development – Building and maintaining backend services that interact with ML models and APIs. API Development – Experience in RESTful API design and implementation using Node.js.

What you will do Build robust backend services and APIs using Python (FastAPI, asyncio) for GenAI workflows and LLM-based systems. Develop and maintain GenAI applications using tools like LangChain, LangGraph, and Cohere, integrating them with custom APIs and data sources. Contribute to systems that enable intelligent routing of prompts, dynamic tool execution, and seamless model-data integration across multiple sources Write clean, modular code for model integration, semantic search, and multi-step agent workflows. Package and deploy applications using Docker and Kubernetes, ensuring scalability and security. Collaborate with data engineers, AI scientists, and infra teams to ship end-to-end features quickly, without sacrificing quality. What you need to succeed Must Have Strong backend development skills in Python Solid understanding of machine learning and generative AI Degree in Computer Science or Engineering Experience deploying services with Docker and Kubernetes in a cloud environment. Familiarity with LLM APIs (OpenAI, Cohere) and how to build prompt-based applications around them. Comfortable writing and debugging PySpark jobs and working with Delta Lake in Databricks. Experience working with Git workflows, CI/CD, and container-based deployments. Nice to Have Experience with LangChain, LangGraph, or other LLM orchestration frameworks. Experience building and deploying MCP Servers, AI Agents Experience with any vector database. Experience with ML FLow

Role overview: Were building a next-gen LLMOps team at Fractal to industrialize GenAI implementation and shape the future of GenAI engineering. This is a hands-on technical leadership role for AI engineers with strong ML and DevOps skills — ideal for those who love building scalable systems from the ground up. You will be designing, deploying, and scaling GenAI and Agentic AI applications with robust lifecycle automation and observability. Required Qualifications: 10 - 14 years of experience in working on ML projects that includes product building mindset, strong hands on skills, technical leadership, leading development teams Model development, training, deployment at scale, monitoring performance for production use cases Strong knowledge on Python, Data Engineering, FastAPI, NLP Knowledge on Langchain, Llamaindex, Langtrace, Langfuse, LLM evaluation, MLFlow, BentoML Should have worked on proprietary and open-source LLMs Experience on LLM fine tuning including PEFT/CPT Experience in creating Agentic AI workflows using frameworks like CrewAI, Langraph, AutoGen, Symantec Kernel Experience in performance optimization, RAG, guardrails, AI governance, prompt engineering, evaluation, and observability Experience in GenAI application deployment on cloud and on-premises at scale for production using DevOps practices Experience in DevOps and MLOps Good working knowledge on Kubernetes and Terraform Experience in minimum one cloud: AWS / GCP / Azure to deploy AI services Team player with excellent communication and presentation skills Must have skills: Product thinking that includes ideation, prototyping, and scale internal accelerators for LLMOps Architect and build scalable LLMOps platforms for enterprise-grade GenAI systems Design and manage end-to-end LLM pipelines from data ingestion and embedding to evaluation and inference Drive LLM-specific infrastructure : memory management, token control, prompt chaining, and context optimization Lead scalable deployment frameworks for LLMs using Kubernetes and GPU-aware scaling Build agentic AI operations capabilities including agent evaluation, observability, orchestration and reflection loops Guardrails & Observability: Implement output filtering, context-aware routing, evaluation harnesses, metrics logging, and incident response Platform Automation for LLMOps: Drive end-to-end automation with Docker, Kubernetes, GitOps, DevOps, Terraform, etc. Product Thinking : Ideate, prototype, and scale internal accelerators and reusable components for LLMOps GenAI Engineering : Productionize LLM-powered applications with modular, reusable, and secure patterns Pipeline Architecture : Create evaluation pipelines — including prompt orchestration, feedback loops, and fine-tuning workflows Prompt & Model Management : Design systems for versioning, AI governance, automated testing, and prompt quality scoring Scalable Deployment : Architect cloud-native and hybrid deployment strategies for large-scale inference Guardrails & Observability : Implement output filtering, context-aware routing, evaluation harnesses, metrics logging, and incident response DevOps & Platform Automation : Drive end-to-end automation with Docker, Kubernetes, GitOps, Terraform, etc. Must-Have Technical Skills LLMOps frameworks : LangChain, MLflow, BentoML, Ray, Truss, FastAPI Prompt evaluation and scoring systems : OpenAI evals, Ragas, Rebuff, Outlines Cloud-native deployment : Kubernetes, Helm, Terraform, Docker, GitOps ML pipeline : Airflow, Prefect, Feast, Feature Store Data stack : Spark/Flink, Parquet/Delta, Lakehouse patterns Cloud : Azure ML, GCP Vertex AI, AWS Bedrock/SageMaker Languages : Python (must), Bash, YAML, Terraform HCL (preferred)

Key Responsibilities: Create, review, and refine Biology questions, explanations, and structured answers Analyze AI-generated Biology content for scientific accuracy and clarity Identify and fix factual or conceptual errors in AI responses Collaborate in training and fine-tuning LLMs through RLHF techniques Required Qualifications: 1+ year of experience in Biology-related domains (Teaching, Research, Content Development, etc ) Strong subject knowledge in Botany, Zoology, Cell Biology, Genetics, Physiology, Ecology, etc Ability to critique and improve AI-generated Biology content Experience with academic or exam-prep content is a plus

About Us: We are a new-age AI solutions firm with an ultra-high-quality talent pool out of India for RLHF Our experts in the specific domain of their expertise help curate hyper-specific LLM datasets We have operations across the US and India and are working with the top AI firms globally to take their large language models (LLMs) to the next level of quality and consistency We are looking for skilled freelance translators who are proficient in Malayalam This role involves translation and content creation If you are fluent in reading, writing/typing, and communicating in Malayalam and are seeking a flexible, remote role, this opportunity is for you! Key Responsibilities: Translate content to Malayalam Create high-quality, culturally relevant written content as needed Maintain consistency, accuracy, and context in all tasks Requirements: Fluency in reading, writing/typing, and understanding in Malayalam Strong translation, and communication skills Previous experience in content creation, transcription, or translation is a plus

Why CDM Smith? Join a team of innovators dedicated to driving data science and AI to new heights. Opportunity to work on impactful projects that shape the future of CDM Smith and the industries we serve. Competitive compensation and benefits package, with opportunities for professional development and growth. About CDM Smith: CDM Smith is dedicated to innovating and driving digital transformation through advanced AI and data science solutions. Our goal is to develop state-of-the-art, industry-leading AI tools that enhance and transform business processes. As a member of our data science team, you will work alongside skilled professionals who are committed to pioneering transformative technologies. Position Summary: We are looking for a skilled and experienced Lead Data Scientist with a strong background in building AI-driven applications and solutions. In this role, you will play a critical role in advancing our generative AI capabilities, creating solutions that streamline processes, and optimizing data insights across the organization. The ideal candidate will be highly analytical, with a deep understanding of machine learning algorithms, advanced data processing techniques, and hands-on experience with Azure Open AI services. Role & responsibilities AI Solution Development: Lead the development and enhancement of AI tools, including generative AI models, natural language processing (NLP) applications, and predictive analytics, that align with CDM Smiths business goals. Machine Learning & Deep Learning : Utilize supervised and unsupervised learning methods to address complex data science challenges. Apply advanced techniques, such as deep learning and neural networks, to optimize model performance. Data Engineering & Processing : Implement and improve data collection methods to ensure robust data pipelines. Focus on building systems that can efficiently process high volumes of data. Data Visualization: Design impactful visualizations using tools such as Power BI, making data insights accessible and actionable for stakeholders. Azure Open AI Expertise : Leverage Azures suite of AI tools, including LLMs and Custom Vision, for scalable, cloud-based deployment of AI solutions. Indexing & Document Optimization : Develop optimized indexing methods and document management strategies for high-volume data handling, especially within Azure Blob storage. Prompt Engineering: Apply prompt engineering techniques to improve the efficiency and accuracy of AI models, focusing on maximizing the effectiveness of LLM-based systems. Cross-functional Collaboration: Work with various teams to identify business challenges, translate them into data science projects, and implement data-driven solutions. Mentorship : Mentor junior data scientists, fostering an environment of growth and continuous learning. Required Qualifications: Educational Background: Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field. Experience: At least 9+ years of relevant experience in data science, with a focus on AI model deployment and application development in a cloud environment, specifically Azure Open AI with at least 2 of those years in a supervisory or leadership capacity. Technical Skills: Proficient in Python and SQL for data manipulation, model building, and analysis. Extensive experience with large language models (LLMs) and RAG architecture. Advanced skills in machine learning algorithms, deep learning, and NLP. Familiarity with Azure Blob storage and optimization techniques for high-volume document processing. Strong data visualization abilities, with proficiency in tools such as Power BI, Tableau, or similar. Problem-Solving Skills: Strong analytical and debugging skills to identify, analyze, and solve complex data challenges. Communication Skills: Ability to communicate complex technical concepts to non-technical stakeholders effectively. Preferred Qualifications Additional Skills: Experience with Azure Custom Vision and related AI tools. Exposure to prompt engineering and document content optimization techniques. Familiarity with data architecture and optimization practices for AI scalability. Soft Skills: Ability to establish and build relationships across departments. Strong organizational skills and attention to detail. Ability to adapt quickly in a dynamic, fast-paced environment.

Technical Lead - Python (AI/ML) - Only Immediate Joiners Permanent Airoli, Mumbai Preferred candidate profile Skillset Requirements: Technical Lead Total overall experience: 6-9 years Experience in Python: 5+ years (should be hands on with development) Experience in AI/ML: 1+ years Experience with Deployment on Cloud: 2+ years If Interested, kindly share me your updated profile along with below details. Full Name: Contact #: Email ID: Total experience: Key skills: Current Location: Relocation: Current Employer: CTC (Including Variable): ECTC: Notice Period: Holding any offer:

Role & Responsibilities: Help in the training of an AI assistant model to enhance its accuracy and performance Evaluate the model's responses across multiple dimensions to ensure quality and relevance Maintain high standards of speed and precision while assessing the model's responses Must Required Traits: Strong attention to detail Ability to carefully follow instructions Excellent proficiency in English