1044 Llm Jobs - Page 16

Job Title: Python AI/ML Engineer Location: Gurugram Experience: 5 to 8 years Job Summary: We are looking for a passionate and skilled Python AI/ML Engineer who brings strong expertise in building AI/ML solutions, productionizing models, and contributing to end-to-end ML pipelines. The ideal candidate should possess deep knowledge of traditional and deep learning concepts, hands-on programming capabilities, experience in enterprise-grade software engineering, and a good understanding of MLOps practices. Key Responsibilities: Design, develop, and deploy scalable machine learning models for classification, regression, NLP, and generative tasks. Build and optimize data transformation workflows using Python and Pandas. Lead AI/ML project pipelines from data ingestion to model deployment and monitoring. Implement model observability, monitoring for drift, and continuous model evaluation. Develop REST APIs and integrate ML models with production systems using frameworks like FastAPI. Participate in code reviews, write unit/integration tests, and ensure high code quality. Collaborate with cross-functional teams including Data Engineers, DevOps, and Product Managers. Stay current with the latest developments in AI, GenAI, ML frameworks, and tools. Use DevOps/MLOps tools to automate and manage model lifecycle processes. Required Skills: Programming & Python Ecosystem: Advanced proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch. Strong understanding of asynchronous programming, FastAPI, and concurrency (Starlette). Deep understanding of multithreading, multiprocessing, and the Python GIL. Ability to write clean, efficient, and testable code. Machine Learning & Deep Learning: Solid grasp of traditional ML concepts: classification, regression, overfitting/underfitting, regularization (L1/L2), multicollinearity. Experience with deep learning: RNNs, attention mechanisms, dropout, early stopping, loss functions (BCE, categorical cross entropy), diffusion models vs GANs. Familiarity with transfer learning and pre-trained model fine-tuning. MLOps: Understanding of ML pipeline design including model training, deployment, and monitoring. Experience in detecting and mitigating data drift and concept drift. Exposure to model observability, monitoring unstructured data drift, and automated drift alerts. Software Engineering & DevOps: Strong skills in REST API development, integration testing, and CI/CD practices. Experience with containerization tools like Docker. Familiarity with cloud-based ML deployment (AWS/Azure) and logging frameworks. Hands-On Problem Solving & Data Engineering: Ability to perform data transformation and aggregation using Python/Pandas. Experience handling dataframes, joins, ranking, filtering, mapping, and custom logic for preprocessing tasks. Nice-to-Have: Experience in GenAI and working with LLMs. Exposure to tools like MLflow, Kubeflow, Airflow, or similar MLOps platforms. Understanding of NLP, embeddings, and transformer-based models. Prior contributions to open-source ML tools or GitHub repositories.

Title: Senior Data Scientist Years of Experience : 8+ years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications Conduct statistical analysis and hypothesis testing for business experimentation Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) Collaborate with data engineering teams to improve data pipelines and quality Document methodologies, build reusable ML components, and publish technical artifacts Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Masters in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage.

Role: #GenAIEngineer Exp: #7Years Location: #Bangalore #Baroda #Chennai #Hyderabad #Pune Solutions using LLM RAG Pipeline OCR Tools (Azure Doc Intelligence / Tesseract / John Snow Labs) Image Pre-processing (denoising / enrichment) in OCR pipeline Frameworks / Platforms - LangChain / LlamaIndex / CrewAI / Semantic Kernel Systematic LLM Model Evaluation Prompt Engineering Agentic Frameworks / MCP / A2A / Function Calling Vector search, embedding models, and semantic retrieval Python Programming Azure AI Services (OpenAI, AI Search, Azure AI Hub, Azure ML Studio) Copilot Studio

About the Role: We are seeking a highly analytical and technically skilled Prompt Engineer to join our team. The ideal candidate will have strong expertise in SQL, a foundational understanding of Python, and a passion for working in the evolving field of Generative AI. Experience in the procurement domain or prompt engineering projects is a strong plus. Key Responsibilities: Design, develop, and test high-quality prompts to interact with large language models (LLMs) and other GenAI tools. Analyze and transform data using advanced SQL queries to support prompt optimization. Collaborate with cross-functional teams including data analysts, engineers, and domain experts to define problem statements and build effective GenAI solutions. Fine-tune and iterate on prompts based on performance metrics and user feedback. Contribute to documentation and share best practices around prompt design and engineering. Required Skills: Strong expertise in SQL capable of writing optimized, complex queries across large datasets. Understanding of Python able to script, manipulate data, and build simple automations or API integrations. Strong problem-solving mindset and attention to detail. Eagerness to explore and work in the field of Prompt Engineering / Generative AI. Preferred Skills: Experience with Prompt Engineering in an academic, hobbyist, or professional setting. Exposure to procurement systems, tools, or workflows . Familiarity with LLM platforms like OpenAI, Claude, or similar. Knowledge of data wrangling and version control tools (e.g., Pandas, Git). Interested candidates can share their updated resume to rolly.martin@thompsonshr.com

We're looking for experienced GenAI Engineers in the following areas: - Architect and implement RAG pipelines (Retrieval-Augmented Generation) - Prompt Engineering - Open-source and proprietary LLMs (like LLaMA, Mistral, Claude, GPT-4o, etc.) - Building AI Agents, MCP, A2A Tech Stack [any other similar to this is also ok]: - LangChain, LangFlow, LangGraph, LangSmith, Dify, AWS bedrock, sageworks, GenAI, - Vector DBs [Postgres, Pinecone, etc] - Agents [A2A] SDK [google, others] and any Agentic AI platform - CrewAI, Cursor, Windsurf, etc

Key Responsibilities: Machine Learning (ML): Design, build, and deploy ML pipelines for structured and unstructured data. Conduct feature engineering , model selection, and hyperparameter tuning. Evaluate model performance using industry-standard metrics and improve accuracy. Collaborate with data engineering teams to ensure clean and accessible data for model training. Apply supervised, unsupervised, and reinforcement learning techniques as per use case. Natural Language Processing (NLP): Develop NLP pipelines for text classification, sentiment analysis, entity recognition, summarization , etc. Leverage libraries like spaCy, NLTK, Hugging Face Transformers, and Gensim . Preprocess and tokenize large corpora using advanced NLP methods. Implement solutions for multi-lingual, domain-specific text data challenges. Integrate NLP services with applications or workflows. Large Language Models (LLM): Fine-tune and deploy LLMs (e.g., GPT, LLaMA, BERT, Falcon, Mistral ) on custom datasets. Use prompt engineering and retrieval augmented generation (RAG) to build intelligent systems. Optimize inference performance and latency for production-level deployment. Stay updated with the latest in GenAI, foundation models, and transformer architectures. Work on use cases like chatbots, question answering, summarization, content generation , and semantic search . Required Skills: Proficiency in Python , PyTorch or TensorFlow , and data science libraries ( scikit-learn , pandas , NumPy ). Experience with NLP frameworks and transformer-based architectures . Exposure to LLM model training/fine-tuning using tools like Hugging Face, LangChain, or OpenAI API. Familiarity with MLOps , model versioning, and deployment using Docker/Kubernetes. Understanding of vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings.

Analyze and triage GitHub issues across trending open-source libraries.Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. codebases locally to assess LLM performance Required Candidate profile Strong exp in Ruby, Proficiency with Git, Docker, & basic software pipeline setup. Ability to understand and navigate complex codebases. Previous participation in LLM research or evaluation projects.

Responsibilities : Design and develop LLM-powered applications using Python and Azure OpenAI services. Extend digital products and platforms, and LLM Apps , with new capabilities Support adoption of digital platforms and LLM Apps, by onboarding new clients Driving automation to expedite and accelerate new client adoption Build end-to-end Retrieval-Augmented Generation (RAG) pipelines , integrating vector databases, semantic search and other related tools. Develop conversational agents and virtual assistants , using frameworks like LangChain or LlamaIndex. Craft effective prompts using advanced prompt engineering and prompt design techniques . Integrate LLMs with external tools, APIs, and business data systems. Apply Agentic AI patterns to RAG and AI Workflows, interacting with LLMs by orchestrating various agents together Deploy and manage applications using Azure Functions , Azure AI services , and serverless components . Ensure performance, scalability, and reliability of AI solutions on Azure. Collaborate across teams and participate in agile development processes. Required Skills (Must Have): Strong proficiency in Python programming language. Expertise in Azure OpenAI Service , including foundation model usage, GPT Model family, and integration. Build and deploy AI solutions leveraging Azure AI services (e.g., Cognitive Services, Azure AI Search). Deep understanding of vector databases and hybrid search capabilities built on top of Azure AI Search Deep experience in prompt engineering , including various prompting strategies (few-shot, chain-of-thought, etc.). Hands-on experience and deep expertise in building RAG pipelines with vector databases and tool integrations. Proven experience developing chatbots or virtual assistants using LLMs. Proficiency in at least one LLM application framework (preferably., LangChain ,). In-depth understanding of LLM models , their capabilities, and applications. Good understanding of LLM evaluations , and how to evaluate LLM model outputs. Experience deploying with Azure Function Apps and broader Azure ecosystem . Solid grasp of API integrations and data workflow design . Solid experience building automation workflows and automation solutions for LLM Apps and Products, to support new client onboarding Solid experience with data and content indexing pipelines to setup new knowledge bases” for RAG and LLM solutions Strong problem-solving skills and ability to deliver scalable, efficient code. Excellent communication and team collaboration abilities. Preferred Skills (Good to Have): Good understanding of using AI Agents and Agentic AI Patterns to integrate with LLMs Familiarity with Multi-Agent AI orchestration and agentic workflows . Experience building cloud-native services with serverless architectures . Understanding of NLP techniques and data transformation pipelines . Familiarity with LLMOps concepts and AI model lifecycle. Qualifications : Bachelor’s degree in computer science, Computer Engineering, or a related field. 3+ years of experience in software development. Experience with LLM applications and cloud platforms. Strong understanding of software development methodologies (e.g., Agile).

Requirement: Role: AI/ML Engineer - Freshers Location: Chennai Notice Period: 0 -15 Days Education: Graduation or Post Graduation in Artificial Intelligence Requirements: Strong foundation in data science concepts and methods. Proficiency in Python for data analysis and developing AI systems. Experience with SQL for querying and managing relational databases. Understanding of Generative AI concepts and practical prompt engineering techniques (creating and optimizing AI prompts for model performance). Familiarity with Generative AI concepts and techniques (such as Large Language Models and Prompt Engineering). Key Skills and Qualifications: Exposure to Generative AI and machine learning concepts and their real-world applications. Familiarity with LangChain Help configure and implement generative AI systems, specifically in the context of large language models (LLMs) and RAG. Basic knowledge of cloud technologies and their role in AI solution deployment. Exposure to GitHub and development practices for cloud-based applications. Preferred skills: Hands-on Experience: Gain practical experience by working with cutting-edge AI technologies like Generative AI, Computer Vision, and Machine Learning/Deep Learning in Academic projects.

Generative AI Engineer Overview We are seeking a visionary GenAI Engineer to lead the design and development of next-generation AI applications using advanced AI services. The ideal candidate will bring deep expertise in GenAI technologies, including Retrieval-Augmented Generation (RAG), intelligent agents, and model fine-tuning, coupled with hands-on experience using tools like LangChain, Model Context Protocol, and Azures full AI stack. Task and Responsibilities: Implement end-to-end Generative AI solutions on the Azure Cloud Platform, leveraging services such as: Azure OpenAI Service, Azure AI Search, Azure Cognitive Services, Azure AI Foundry, Azure Machine Learning etc. Creating data pipelines to ingest, process, and prepare data for analysis and modeling using Azure services, such as Azure AI Document Intelligence , Azure Databricks etc. Design and deploy RAG pipelines, incorporating structured and unstructured data to enhance LLM-based applications. Develop and orchestrate AI Agents and Autonomous Agents for real-time decision-making, task and automation. Fine-tune and optimize Small Language Models ( SLMs ) for domain-specific applications with a focus on performance, cost, and inference latency. Integrate LLMs/SLMs into applications using frameworks such as LangChain , Model Context Protocol ( MCP ), etc. Collaborate with data scientists, ML engineers, and product teams to align AI capabilities with business goals. Lead technical discussions and create architecture blueprints, best practices, and governance models for GenAI adoption across the enterprise. Monitor and optimize deployed solutions for scalability, latency, security, and compliance. Qualifications: Bachelor's or master's degree in computer science, Data Science, AI/ML, information technology, or a related field. Overall 8+ years’ combined experience in IT, 5+ years of experience in AI/ML solution engineering with at least 2+ years focused on Generative AI. Strong experience with LLMs and SLMs, including integration of open source models, prompt engineering, evaluation, and fine-tuning techniques. Proven track record using LangChain, Semantic Kernel, RAG, AI Agents, and MCP (Model Context Protocol) in production environments. Solid understanding and Hands-on experience with vector databases, embeddings, and Azure AI Search integration for semantic retrieval. Hands-on experience with tools like MLFlow, Azure Machine Learning, Azure OpenAI Service, Azure AI Search, Azure Cognitive Services, Azure AI Foundry, Azure Machine Learning etc. Familiarity with MLOps, CI/CD pipelines, and responsible AI practices. Experience deploying AI models on Azure Kubernetes Services (AKS) or Azure Container Apps. Understanding of security and compliance in AI deployments (e.g., data privacy, bias detection). Proficiency in programming languages like Python (essential). Excellent problem-solving, analytical, and critical thinking skills. Strong communication and collaboration skills to work effectively in a team environment. A passion for innovation and a desire to push the boundaries of what's possible with Gen AI. Relevant industry certifications, such as Microsoft Certified: Azure AI Engineer, Azure Solution Architect etc. is a plus.

Experienced Male from Real Estate to take care of all Legal activities. Legal advise on issues, Agreements, Land Acquisitions, RERA Registrations & compliance's, Litigations, Court appearances, Documentation & court papers etc. etc.

Job Description:- We are seeking an experienced AI Engineer to join our team and play a key role in developing and integrating cutting-edge AI tools into our SaaS products. The ideal candidate has hands-on expertise with platforms like OpenAI, LangChain, or Hugging Face, and a strong background in delivering scalable, production-ready AI solutions. In this role, you will lead AI feature development, collaborate cross-functionally, and mentor junior engineers. Responsibilities:- Design and develop AI-driven features leveraging large language models (LLMs) and embedding techniques. Integrate solutions using tools such as OpenAI, vector databases (e.g.,Pinecone, FAISS), and generative AI frameworks like LangChain or HuggingFace. Build and maintain Retrieval-Augmented Generation (RAG) pipelines and conversational AI workflows. Collaborate closely with backend and frontend engineering teams to ensure seamless integration of AI capabilities into the product. Continuously optimize AI models and pipelines for performance, scalability, and accuracy. Requirements: 2-4 years of experience in AI/ML-focused software development Proficiency in Python and hands-on experience with AI frameworks and toolkits such as LangChain, Pinecone, and OpenAI Strong problem-solving abilities and solid understanding of system architecture and design Excellent communication and collaboration skills

Seeking a GenAI Software Engineer with 5+ years’ experience to develop LLM-based applications, RAG, and AI agents. Must be skilled in LangChain, vector databases, and cloud-based AI deployment in agile teams. Required Candidate profile Experienced AI developer with expertise in GenAI, LLM apps, and RAG. Proficient in LangChain, vector DBs, and cloud AI services. Strong collaboration and agile development background preferred.

Role and Responsibilities: Development, deployment, and optimization of ML, NLP models, and LLM/GenAI solutions Develop and maintain Python-based ML pipelines and manage associated databases Deploy AI models on Azure/AWS, ensuring performance and scalability Mentor team members and stay updated on advancements in ML, NLP, and GenAI Implement LLMOps best practices for efficient model lifecycle management Suitable candidates can share their resume at hr41@hectorandstreak.com

Data Science Consultant Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. Whats more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound social impact as a Data Science Consultant on our Data Science Team in Bangalore. What youll achieve SRS Automation is an innovative team aiming to streamline and automate manual heavy processes within the Dell Sales Renewals organization. The team employs creative technologies tailored for each project requirement including RPA, Python, Database query, generative and agentic AI, microservice development and PowerBI for reporting. Dell data security and solid coding standards and procedures are a critical part of how we operate. The team has a large portfolio of automated solutions that are both developed and maintained to ensure continuous efficiency delivery. As a Data Science Consultant, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also collaborate with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines. You will: Develop and fine-tune domain-specific language models using LLMs Build agents that work with LLMs and agentic workflows Perform data analytics and present findings effectively Integrate applications and ensure seamless functionality and collaborate with team members and work independently Research and stay up-to-date with the latest developments in AI and Ensure adherence to security and coding standards Take the first step towards your dream career Every Dell Technologies team member brings something unique to the table. Heres what we are looking for with this role: Essential Requirements 12 to 15 years of related work experience in Data Science. Proficiency in Python programming Experience with application integration Knowledge of transformers and LLMs. Solid data analytics skills and ability to present findings Ability to fine-tune LLMs for domain-specific language and experience in building agents and agentic workflows Desirable Requirements Solid knowledge of Azure Work experience in a DevOps RPA team Who we are We believe that each of us has the power to make an impact. Thats why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you. Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us. Application closing date: 31-Jul-2025 Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here. If Interested, please apply using the link : https://dell.wd1.myworkdayjobs.com/External/job/Bangalore-India/Consultant--Data-Science--I9-_R270197

About the company: ARAs client TechGlobal (pseudonym) is a global leader in strategy, technology consulting and digital services, enabling clients in more than 100+ countries to implement cutting edge solutions in their transformation journey. TechGlobal helps businesses become digital-first and digital-ready. The company has a global presence with 600000+ employees ( 200000+ in India). India is a focus for them with their Development Centres presence in over 10 locations across Tier 1 and Tier 2 cities. They are recognised for their people first and employee oriented policies. Along with offering hybrid work options, a Pan India presence gives flexible location options to employees. About the role: As an AI / ML Engineer, you will be responsible for developing applications and systems that utilize AI tools, cloud-based AI services, and on-premise or cloud-native application pipelines. The ideal candidate will have a strong foundation in deploying production-ready AI solutions and integrating Generative AI (GenAI) models into business applications. Key Responsibilities: Serve as a Subject Matter Expert (SME) in AI/ML technologies. Lead, mentor, and collaborate with team members to ensure successful project delivery. Make key technical and strategic decisions across multiple teams. Design, build, and deploy scalable AI/ML solutions in production environments. Integrate large language models (LLMs) and generative AI solutions into enterprise systems. Engage in regular cross-functional collaboration to align AI/ML solutions with business goals. Conduct training sessions and facilitate knowledge sharing within the team. Ensure timely project execution in alignment with organizational strategy. Must-Have Skills: Expertise in Large Language Models (LLMs) and their practical applications. Deep knowledge of deep learning frameworks such as TensorFlow and PyTorch. Proven experience deploying AI models on cloud platforms such as AWS, Azure, or Google Cloud. Strong grasp of natural language processing (NLP) techniques and tools. Ability to develop production-grade, scalable AI solutions. Good-to-Have Skills: Experience with tools like Hugging Face Transformers or LangChain. Exposure to MLOps pipelines and containerization (Docker/Kubernetes). Familiarity with RESTful APIs, version control (Git), and CI/CD pipelines. Experience and Qualifications Candidates must have a minimum of 7.5 years of experience in AI/ML roles, with a strong focus on Large Language Models. A 15-year full-time education background is mandatory

Key Responsibilities: Design and implement AI solutions using large language models (LLMs) for tasks such as summarization, question answering, and document understanding. Build and optimize retrieval-augmented generation (RAG) pipelines combining OCR and LLMs for unstructured document processing. Integrate LLMs and OCR tools (e.g., Azure Document Intelligence, Tesseract) into scalable applications. Preprocess scanned and digital documents using OCR to extract structured and semi-structured text for LLM input. Perform prompt engineering and fine-tuning of LLMs to enhance accuracy and task-specific performance. Evaluate and monitor LLM+OCR system outputs for quality, bias, and hallucination risks. Collaborate with cross-functional teams to deliver AI solutions tailored to domain-specific needs. Stay updated on the latest developments in foundation models, Agentic AI and OCR technologies. Required Skills: Hands-on experience with LLM frameworks such as LangChain, Semantic Kernel. Strong understanding of vector search, embedding models, and semantic retrieval (e.g., FAISS, Pinecone, Azure Cognitive Search). Proficiency in Python, with experience integrating APIs, Function Calling, Regular Expression, and handling LLM outputs. Deep expertise in prompt engineering, including few-shot prompting, prompt tuning, prompt chaining, and optimization techniques for task-specific accuracy and cost control. Solid knowledge of RAG architectures and agent design patterns (e.g., tool use, memory, planning). Experience with OCR technologies (e.g., Tesseract, Azure Document Intelligence) for document understanding and information extraction from scanned or image-based content. Familiarity with LLM platforms and tools like Azure OpenAI, LLMOps. Experience deploying LLM-based applications in cloud environments, with attention to performance, reliability, and scalability. Practical understanding of SAFe Agile methodologies, with experience delivering AI/ML solutions in cross-functional Agile teams. Proven ability to work independently without supervision, demonstrating initiative, ownership, and accountability across all phases of solution development.

We are seeking an innovative and forward-thinking AI Strategist to join our team. In this role, you will lead the development and implementation of AI-driven strategies that align with our organization's long-term goals. You will work closely with cross-functional teams to identify opportunities where artificial intelligence can drive business growth, operational efficiency, and competitive advantage. Role & responsibilities Required Skills: Proven experience with Large Language Models (e.g., GPT, BERT, LLaMA) and customizing them for business-specific use cases. Proficient in AI code tools, including GitHub Copilot, Cursor, and more. Expertise in prompt engineering and prompt optimization for effective LLM outputs. Strong understanding of security principles, specifically concerning LLM implementation and internal data protection Preferred candidate profile LLM Model Customization & Implementation Customize and fine-tune Large Language Models (LLMs) to address specific business and functional requirements. Design and implement LLM integrations to optimize business workflows and support various functional areas, ensuring high-quality and relevant outputs. Conduct regular assessments to maintain alignment with organizational goals and security standards, preventing any unintended exposure to external networks.

We are looking for immediate joiners only We are seeking an innovative and forward-thinking AI Strategist with .Net/Java Full stack to join our team. In this role, you will lead the development and implementation of AI-driven strategies that align with our organization's long-term goals. You will work closely with cross-functional teams to identify opportunities where artificial intelligence can drive business growth, operational efficiency, and competitive advantage. Role & responsibilities Required Skills: We are looking for a Full Stack Architect / Associate Architect with strong architectural expertise and deep hands-on experience across Angular, .NET Core, SQL Server, and especially IIS . The ideal candidate must be proficient in application architecture design , performance tuning , and end-to-end ownership of enterprise-grade solutions with significant exposure to hosting and configuration environments. Key Responsibilities Architect, design, and deliver high-performance enterprise applications using Angular, .NET Core, and SQL Server. Define and implement best practices around coding, architecture, security, and performance. Take complete ownership of IIS setup, deployment pipelines , and application hosting architecture , ensuring secure and scalable configuration. Troubleshoot and resolve issues related to Windows Authentication, Application Pools, and service account connectivity. Proven experience with Large Language Models (e.g., GPT, BERT, LLaMA) and customizing them for business-specific use cases. Proficient in AI code tools, including GitHub Copilot, Cursor, and more. Expertise in prompt engineering and prompt optimization for effective LLM outputs. Strong understanding of security principles, specifically concerning LLM implementation and internal data protection Preferred candidate profile LLM Model Customization & Implementation Customize and fine-tune Large Language Models (LLMs) to address specific business and functional requirements. Design and implement LLM integrations to optimize business workflows and support various functional areas, ensuring high-quality and relevant outputs. Conduct regular assessments to maintain alignment with organizational goals and security standards, preventing any unintended exposure to external networks.

Job Title: Senior AI Engineer LLM Infrastructure & Tooling Location: Remote / Hybrid / Onsite (as applicable) Experience: 7+ Years in Software Engineering | 1+ Year with LLMs in Production Key Responsibilities: Build core AI components (frontend & backend) including observability and feedback tools. Develop and optimize LLM-powered APIs , vector search tools, and orchestration workflows. Monitor performance, reliability, and safety of AI agents and design improvement feedback loops. Identify gaps in tooling and standardize best practices for deploying and maintaining AI services. Collaborate with product, infrastructure, and data teams to ensure reusability and scalability of AI solutions. Stay updated on emerging LLMs, retrieval methods, and modern deployment techniques. Must-Have Skills: 7+ years of hands-on software development experience, with 5+ years in building cloud-based web applications. 1+ year experience working with LLMs in production environments. Proficient in TypeScript or other typed programming languages. Solid understanding of transformer models , agent architectures , and attention mechanisms . Experience with cloud infrastructure and full-lifecycle AI/ML system deployment. Strong problem-solving and stakeholder communication skills. Good to Have: Experience with RAG systems , vector databases, chunking strategies. Familiarity with semantic search and LLM evaluation frameworks . Exposure to frontend development , particularly in scalable, modular AI interfaces. Background in documenting technical trade-offs and performance benchmarks.

You will work closely with data scientists, product teams, and developers to fine-tune LLM behavior for diverse applications including chatbots, code generation, creative writing, and data extraction.

Responsibilities: * Collaborate with cross-functional teams on data science projects * Implement Keras models for machine learning applications * Develop AI/ML solutions using Python, Keras, LLM, Data Science

Role Overview :- Monitor, evaluate, and optimize AI/LLM workflows in production environments. Ensure reliable, efficient, and high-quality AI system performance by building out an LLM Ops platform that is self-serve for the engineering and data science departments. Key Responsibilities:- Collaborate with data scientists and software engineers to integrate an LLM Ops platform (Opik by CometML) for existing AI workflows Identify valuable performance metrics (accuracy, quality, etc) for AI workflows and create on-going sampling evaluation processes using the LLM Ops platform that alert when metrics drop below thresholds Cross-team collaboration to create datasets and benchmarks for new AI workflows Run experiments on datasets and optimize performance via model changes and prompt adjustments Debug and troubleshoot AI workflow issues Optimize inference costs and latency while maintaining accuracy and quality Develop automations for LLM Ops platform integration to empower data scientists and software engineers to self-serve integration with the AI workflows they build Requirements:- Strong Python programming skills Experience with generative AI models and tools (OpenAI, Anthropic, Bedrock, etc) Knowledge of fundamental statistical concepts and tools in data science such as: heuristic and non-heuristic measurements in NLP (BLEU, WER, sentiment analysis, LLM-as-judge, etc), standard deviation, sampling rate, and a high level understanding of how modern AI models work (knowledge cutoffs, context windows, temperature, etc) Familiarity with AWS Understanding of prompt engineering concepts People skills: you will be expected to frequently collaborate with other teams to help to perfect their AI workflows Experience Level 3-5 years of experience in LLM/AI Ops, MLOps, Data Science, or MLE

Key Responsibilities: Architect and implement advanced AI solutions leveraging LLMs (and otheremerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI). Develop and refine AgenticAI systems focusingon planning, memory,tool utilization, and dynamic task critic execution. Engineer and optimize prompt engineering pipelines to achieve superioraccuracy and low latency across diverse applications. Fine-tune and deploy specialized LLMs and AI copilots to transform engineering and business operations. Collaborate with cross-functional teams to deliverproduction-grade solutions that create tangible value. Stay ahead of the curve by integrating emergingGenAI research and state-of-the-art capabilities into practical, real-world systems. Lead projects and mentor junior engineers, contributing to a culture of innovation and growth Required Qualifications: Experience: 3-8 years of hands-on ML/AI/Deep Learning experience, with a strong portfolio of real world application development. Technical Proficiency: Advanced Python skills and extensive experience with leading AI tools and libraries (OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow). Core Knowledge: Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.g., FAISS, Weaviate). Prompt Engineering Mastery: Proven expertise in designing and implementing effective, reusable prompts for complex reasoning, classification, generation, and tool integration tasks across a wide variety of models including open-source solutions. Agentic AI Acumen: Prior experience with autonomous AI agents or multi-agent orchestration is a significant advantage. \ Mindset: A startup-ready attitude - agile, intellectually curious, and hands-on, thriving in fast paced, iterative environments Role & responsibilities

ML Engineer is responsible to discover the information hidden in vast amounts of data and help us make smarter decisions to deliver better products. Your primary focus will be in applying machine learning techniques for data mining and statistical analysis, Text analytics using NLP/LLM and building high quality prediction systems integrated with our products. Job Responsibilities: Building models using best in class ML technology including LLMs. Training/fine tuning models with new/modified training dataset. Selecting features, building, and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods Processing, cleansing, and verifying the integrity of data used for analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Technical skills Mandatory 5 to 10 years of experience as Machine Learning Engineer with strong Python skill. Graduate in Engineering, Technology along with good business skills Good scripting and programming skills in Python Excellent understanding of machine learning techniques and algorithms including knowledge about LLM like GPT, Llama, Claude, or Anthropic models etc. Experience with NLP. Knowledge about applied statistics skills, such as distributions, statistical testing, regression, etc. Basic understanding of NoSQL databases, such as MongoDB, Cassandra. Nice to have Exposure to financial research domain Experience with JIRA, Confluence Understanding of scrum and Agile methodologies Experience with data visualization tools, such as Grafana, power BI, GGplot, etc. Soft skills Oral and written communication skills Good problem solving and negotiation skills Passion, curiosity and attention to detail