219 Llms Jobs - Page 7

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

We are seeking a AI Product Manager to take ownership of defining, building, and scaling our core products. In this role, you will act as the bridge between technical teams (engineering, AI/ML) and business stakeholders.

Position - Lead Machine Learning Engineer- MLOps, VertexAI, LLMs, GenAI, ML Model Management Role Overview UPS Data Science and Machine Learning team is seeking a highly skilled and experienced Lead Machine Learning Engineer to manage our AI, ML, GenAI application focused on Cross Border logistics. This position leverages continuous integration and deployment of the best practices, including test automation and monitoring, to ensure successful deployment of optimal ML models and analytical systems. You will be responsible for the end-to-end lifecycle of AI models, from experimentation and fine-tuning to deployment and management in production. A strong background in prompt engineering and practical experience with either Google Cloud's Vertex AI platform is essential for this role. You will also provide technical leadership and mentorship to other members of the AI/ML team. Key Responsibilities Lead the development and deployment of generative AI solutions utilizing LLMs, SLMs, and FMs for various applications (e.g., content generation, chatbots, summarization, code generation, etc.). Architect and implement robust and scalable infrastructure for training, fine-tuning, and serving large-scale AI models, leveraging either Vertex AI. Drive the fine-tuning and adaptation of pre-trained models using proprietary data to achieve state-of-the-art performance on specific tasks. Develop and implement effective prompt engineering strategies to elicit desired outputs and control the behavior of generative models. Manage the lifecycle of deployed models , production support, including monitoring performance, identifying areas for improvement, and implementing necessary updates or retraining. Collaborate closely with cross-functional teams (e.g., product, engineering, research) to understand business requirements and translate them into technical solutions. Provide technical leadership and mentorship to junior machine learning engineers, fostering a culture of learning and innovation. Ensure the responsible and ethical development and deployment of AI models , considering factors such as bias, fairness, and privacy. Stay up to date with latest advancements in generative AI, LLMs, and related technologies, and evaluate their potential application within the company. Document technical designs, implementation details, and deployment processes. Troubleshoot and resolve issues related to model performance and deployment. Required Skills and Experience: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Minimum of 5-8 years of hands-on experience in building, deploying, and managing machine learning models in a production environment. Demonstrable experience in managing, deploying, and fine-tuning large language models (LLMs), small language models (SLMs), and foundation models (FMs). Significant hands-on experience with prompt engineering techniques for various generative AI tasks. Proven experience working with either Google Cloud's Vertex AI platform platform . including experience with their respective model registries, deployment tools, and MLOps features. Strong programming skills in Python and experience with relevant machine learning libraries (e.g., TensorFlow, PyTorch, Transformers). Experience with cloud computing platforms (beyond Vertex AI is a plus, e.g. Azure). Solid understanding of machine learning principles, deep learning architectures, and evaluation metrics. Excellent problem-solving, analytical, and communication skills. Ability to work independently and as part of a collaborative team. Experience with MLOps practices and tools for continuous integration and continuous delivery (CI/CD) of ML models is highly desirable. Experience with version control systems (e.g., Git). Bonus Points: Experience with model governance frameworks and implementing ethical AI practices. Experience with specific generative AI use cases relevant to Logistics industry. Publications or contributions to open-source projects, technical blogs, or industry conferences are considered a plus Familiarity with data engineering pipelines and tools. Familiarity with emerging trends in generative AI, reinforcement learning from human feedback (RLHF), and federated learning approaches.

Hi all, We are hiring for the role Generative AI Engineer Experience: 3 - 6 Years Location: Bangalore Notice Period: Immediate - 15 Days Skills: Generative AI Engineer Position Overview: We are looking for a Generative AI Engineer with expertise in Azure OpenAI and hands-on experience with models such as GPT-4o, GPT-o1, and open source LLMs like Llama, mistral. You will work on GenAI solutions development, RAG, fine-tuning, and deploying resources in Azure environment. Proficiency in prompt engineering, Python, PostgreSQL, FastAPI, Streamlit, Django and Angular is essential. This role also requires strong skills in AI models orchestration using intent mapping, Semantic Kernel or function calling, along with proficiency in presentation and public speaking. Key Responsibilities: • RAG, fine-tune, and deploy Azure OpenAI models (e.g., GPT-4o, GPT-o1) and other open-source large language models (LLMs). • Build AI-powered applications using frameworks such as FastAPI, Streamlit, Django, and Angular. • Design and execute AI workflows using tools like prompt flow, Semantic Kernel and implement function calling for complex use cases. • Conduct prompt engineering to improve model performance for specific business cases. • Visualize data and create user interaction insights using Power BI. • Ensure smooth deployment and maintenance of models on Azure cloud infrastructure, including scalability and optimization. • Prepare and deliver presentations, demos, and technical documentation to internal and external stakeholders. • Stay updated with advancements in generative AI, NLP, and machine learning to continuously improve models and methodologies. Required Skills & Qualifications: • Bachelors degree in Computer science, Artificial intelligence, Machine learning, or related field. • At least 2+ year of hands-on experience working on generative AI projects. • Strong expertise in Azure OpenAI models (GPT-4o, GPT-3.5, GPT-o1 etc.). • Proficient in Prompt Engineering, Python, Streamlit, Django, FastAPI, and Angular. • Basics of html, css, javascript, typescript and angular. • Basic understanding of neural networks, machine and transformer architectures. • Experience in retrieval-augmented generation (RAG) and fine-tuning Large language models. • Familiarity with AI model orchestration tools such as Semantic Kernel, intent mapping and function calling techniques. • Excellent public speaking and presentation skills to convey technical concepts to business stakeholders. • Azure Certified AZ900 or AI900 Preferred Qualifications: • Masters degree in Artificial Intelligence, Machine Learning, or related field. • At least 3+ years of experience working on generative AI, NLP, and machine learning projects. • Strong understanding of neural networks, machine learning and transformer architectures. • Implemented GenAI solutions in production. • Familiarity with Automotive Industry • Hands on experience in RAG, RAFT and optimized fine-tuning. • Azure Certified AI-102, DP-100, AZ-204 or DP-203 If you are interested drop your resume at mojesh.p@acesoftlabs.com Call: 9701971793

Develop Deep Learning models, focusing on NLP, Large Language Models (LLMs), and Generative AI. Expertise in NLP techniques (e.g., text classification, sentiment analysis, text generation).

Generative AI Engineer Python and FastAPI,deploying generative AI models (LLMs, GANs, VAEs) in production environmentsRAG, embeddings,RESTful APIsmanaging secure APIDocker and KubernetesSQL and NoSQL databases(AWS, Azure, GCP)

* If you are 5+ years experienced and Immediate joiner , please apply: https://docs.google.com/forms/d/e/1FAIpQLScorR1zEgu9FvDHO-4gjJEOPhk_2tJE6cgftARiy9rwcVcDHg/viewform 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Interview Pattern: Screening Interview - 30 min on google meet Second Interview - 60 min Final Client Interview - 30 min Govt Id should be shown in all interviews and camera is a must. Timings: 8 hrs/day, Mon-Fri Salary will be competitive above the market standards and will be calculated on hourly basis. Role & responsibilities Preferred candidate profile : Immediate Joiners

Responsibilities • Design and develop AI models and algorithms • Build and train ML systems • Process large datasets • Deploy models to production • Collaborate with team to integrate AI solution • Ensure model accuracy • Stay updated with AI trends

Software Engineer L2 (Chatbot Engineering) Python and Django AWS RDBMS/NoSQL frontend, and LLMs, GenAI

AI Model Deployment & Integration: Deploy and manage AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems). Implement automated CI/CD pipelines for seamless deployment and scaling of AI models. Ensure efficient model integration into existing enterprise applications and workflows in collaboration with AI Engineers. Optimize AI infrastructure for performance and cost efficiency in cloud environments (AWS, Azure, GCP). Monitoring & Performance Management: Develop and implement monitoring solutions to track model performance, latency, drift, and cost metrics. Set up alerts and automated workflows to manage performance degradation and retraining triggers. Ensure responsible AI by monitoring for issues such as bias, hallucinations, and security vulnerabilities in GenAI outputs. Collaborate with Data Scientists to establish feedback loops for continuous model improvement. Automation & MLOps Best Practices: Establish scalable MLOps practices to support the continuous deployment and maintenance of AI models. Automate model retraining, versioning, and rollback strategies to ensure reliability and compliance. Utilize infrastructure-as-code (Terraform, CloudFormation) to manage AI pipelines. Security & Compliance: Implement security measures to prevent prompt injections, data leakage, and unauthorized model access. Work closely with compliance teams to ensure AI solutions adhere to privacy and regulatory standards (HIPAA, GDPR). Regularly audit AI pipelines for ethical AI practices and data governance. Collaboration & Process Improvement: Work closely with AI Engineers, Product Managers, and IT teams to align AI operational processes with business needs. Contribute to the development of AI Ops documentation, playbooks, and best practices. Continuously evaluate emerging GenAI operational tools and processes to drive innovation. Qualifications & Skills: Education: Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or a related field. Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus. Experience: 3+ years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions. Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments. Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI. Technical Skills: Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow. Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking. Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads. Familiarity with automation scripting using Python, Bash, or PowerShell. Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization. Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment. Strong understanding of AI security principles, including data privacy and governance considerations.

NLP & Data Engineer - Risk Insights & Monitoring Engagement Type: Contract Contract Duration: 6 Months Domain: Banking / Finance Number of Openings: 1 We are seeking a highly skilled and experienced NLP & Data Engineer to contribute to our Risk Insights & Monitoring platform within the Banking/Finance sector. The ideal candidate will have a strong background in designing, implementing, and deploying state-of-the-art NLP models, coupled with robust data engineering capabilities and a passion for building high-quality, scalable software solutions. You will play a crucial role in leveraging natural language processing to extract valuable insights from unstructured data. Key Responsibilities: NLP Model Development & Implementation: Design and implement cutting-edge NLP models for tasks such as text classification, semantic search, sentiment analysis, named entity recognition (NER), and summary generation. Conduct thorough data preprocessing and feature engineering to enhance model accuracy and performance. Stay abreast of the latest developments in NLP and Machine Learning, integrating advanced techniques into our solutions. (Plus) Prior experience in agentic AI, Large Language Models (LLMs), prompt engineering, and generative AI. Data Engineering & Backend Development: Implement and deliver high-quality software solutions/components for the Credit Risk monitoring platform. Develop backend services and microservices using Java Spring Boot, J2EE, and REST APIs , ensuring high SLA for data availability and data quality. Proficiency in programming languages such as Python and Java , with experience in frameworks like TensorFlow, PyTorch, or Keras. Experience with data handling and processing tools like Pandas, NumPy, and SQL . Knowledge of SQL and PL/SQL (Oracle) and UNIX , including writing queries, packages, working with joins, partitions, looking at execution plans, and tuning queries. Cloud & DevOps: Experience building cloud-ready and migrating applications using Azure , with a strong understanding of Azure Native Cloud services, software design, and enterprise integration patterns. Experience using DevOps toolsets like GitLab and Jenkins . Build observability into solutions, monitor production health, assist in resolving incidents, and remediate the root cause of risks and issues. Strong desire to work with baked-in quality disciplines such as TDD (Test-Driven Development), BDD (Behavior-Driven Development), test automation, and DevOps principles. Collaboration & Mentoring: Collaborate closely with data scientists, software engineers, and product managers to align NLP projects with business objectives. Mentor developers, review code, and ensure adherence to best practices and standards. Share knowledge and expertise with colleagues, contribute to hiring, and actively participate in our engineering culture and internal communities. Quality & Compliance: Apply a broad range of software engineering practices, from analyzing user needs and developing new features to automated testing and deployment. Ensure the quality, security, reliability, and compliance of solutions by applying digital principles and implementing both functional and non-functional requirements. Stakeholder Management: Understand, represent, and advocate for client needs. Take ownership of assigned tasks through to ultimate resolution. Ensure accuracy and timeliness of delivering solutions using the best IT standards and practices. Expertise & Qualifications: Total Years of Experience: 8 to 10 years. Relevant Years of Experience: 5 to 8 years. Education: Bachelor of Engineering or equivalent. Domain Specific Experience: Ideally 8-10 years of experience in NLP-based applications focused on the Banking/Finance sector. Preference for experience in financial data extraction and classification. Mandatory Skills: NLP, Python . Desired Skills: SQL, Azure . Analytical & Communication: Strong analytical and problem-solving skills with the ability to think critically and creatively. Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders. Learning Agility: Interested in learning new technologies and practices, reusing strategic platforms and standards, evaluating options, and making decisions with long-term sustainability in mind. Agile Mindset: Passion for and experience with Agile working practices. Additional Information: Approx. Vendor Billing Rate: INR 16,000 per day. Background Check: As per client policy.

Were seeking a forward-thinking Gen AI Engineer to design, implement, and optimize cutting-edge agentic AI solutions using frameworks such as Crew.ai , LangChain , and LangGraph . You will work at the intersection of LLMs , Retrieval-Augmented Generation (RAG) systems, and NLP , enabling impactful AI applications across diverse domains. Key Responsibilities Design and deploy autonomous AI agents and multi-agent systems using LLMs such as GPT-4o, Claude, and LLaMA, leveraging Crew.ai, LangChain (and LangGraph). Own the AI solution lifecycle , including data acquisition, model experimentation, fine-tuning, deployment, and production monitoring. Develop scalable AI backends and pipelines using Python with frameworks like PyTorch or TensorFlow, deploying via REST APIs (FastAPI) on cloud platforms like AWS or Azure. Implement RAG-based systems by integrating open-source LLMs (via Hugging Face or Ollama) with vector databases (e.g., Pinecone, ChromaDB) and structured data stores (SQL/NoSQL). Collaborate with cross-functional teams to ensure reliable, maintainable, and impactful AI solutions. Required Skills & Experience 2 to 5 years of experience in AI/ML, NLP, Generative AI, with a focus on agentic AI systems . Strong proficiency in Python and hands-on experience building RAG systems and deploying open-source LLMs. Experience developing AI-driven backends and services with a strong understanding of scalability and performance. Familiarity with vector search technologies, database integration, and cloud-native architectures. Excellent communication and collaboration skills; ability to work effectively in a team environment. Education B.Tech/B.E. or M.Tech/M.E. in Computer Science, AI/ML, or a related field. Role: Gen AI Engineer Designation: AI Developer Experience: 2-5 Years (AI/ML, NLP, Generative AI): Location: Pune

What You'll Do We are looking for experienced Machine Learning Engineer with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities as a Senior Technical Lead will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will be reporting to Senior Manager, Software Engineering What Your Responsibilities Will Be You have a blend of technical skills in the fields of AI & Machine Learning especially with LLMs and a deep-seated understanding of software development practices where you'll work with a team to ensure our systems are scalable, performant and accurate. We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Inspire creativity by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards, contributing to the project's. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful 8+ years of experience building Machine Learning models and deploying them in production environments as part of creating solutions to complex customer problems. Bachelor's degree with computer science exposure Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. With technological innovations in AI & ML(esp. GenAI). Expertise in design patterns, data structures, distributed systems, and experience with cloud technologies. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, Grafana This is a remote role.

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

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

Greetings from Blue Altair! Job Overview: We are seeking an experienced and highly skilled Data Science and AI Engineer to join our dynamic team. The ideal candidate will have 5+ years of experience working on cutting-edge data science and AI technologies across various cloud platforms with a strong focus to work on LLMs and SLMs. The role demands a professional capable of performing in a client-facing environment, as well as mentoring and guiding junior team members. Title: Consultant/Sr. Consultant - Data Science Engineer Experience : 5-8 years Location: Pune/Bangalore (Hybrid) Roles and responsibilities: Develop, implement, and optimize machine learning models and AI algorithms to solve complex business problems. Design, build, and fine-tune AI models, particularly focusing on LLMs and SLMs, using state-of-the-art techniques and architectures. Apply advanced techniques in prompt engineering, model fine-tuning, and optimization to tailor models for specific business needs. Deploy and manage machine learning models and pipelines on cloud platforms (AWS, GCP, Azure, etc.). Work closely with clients to understand their data and AI needs and provide tailored solutions. Collaborate with cross-functional teams to integrate AI solutions into broader software architectures. Mentor junior team members and provide guidance in implementing best practices in data science and AI development. Stay up-to-date with the latest trends and advancements in data science, AI, and cloud technologies. Prepare technical documentation and present insights to both technical and non-technical stakeholders. Requirement: 5+ years of experience in data science, machine learning, and AI technologies. Proven experience working with cloud platforms such as Google Cloud, Microsoft Azure, or AWS. Expertise in programming languages such as Python, R, Julia, and AI frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging face Transformers. Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Tableau) Solid understanding of data engineering concepts including ETL, data pipelines, and databases (SQL, NoSQL). Experience with MLOps practices and deployment of models in production environments. Familiarity with NLP (Natural Language Processing) tasks and working with large-scale datasets. Hands-on experience with generative AI models like GPT, Gemini, Claude, Mistral etc. Client-facing experience with strong communication skills to manage and engage stakeholders. Strong problem-solving skills and analytical mindset. Ability to work independently and as part of a team and mentor and provide technical leadership to junior team members.

As the Engineering manager, you will be managing the roadmap priorities for AI/MLSolution andwill bepoint of contactfor all technical issues and decisions, while managing stakeholders and partners across the organization. Provide technical leadership manage a high-performing engineering team to build and scale our next generationAI Solutions. Hire and directly lead a diverse team of top-tier ML and software engineers, taking charge of allfacetsof AI Products Design, Build,optimize, fine-tune Generative AI/LLM models/AI Solutions that can be integrated withnumerousapplications, support thousands of tenants, andoperateat scale in production to support variousPaypalAI Personalization initiatives Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Drive innovation by researching and incorporatingstate-of-the-artmachine learning techniques, tools, and frameworks into the platform. Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Collaborate with cross-functional teams including product managers, data scientists, and software engineers and stakeholders to define platform requirements and priorities. Develop and evolve engineering processes and collaboration models tooptimizeteam efficiency and collaboration Mentor team members,providetechnical guidance, and foster a culture of collaboration, innovation, and continuous learning. Stay up to date with the latest advancements in AI/ML technology and industry trends andleveragethis knowledge to enhance the platforms capabilities What Do You NeedtoBring Qualifications Proven experience in leading or managing machine learning/AI teams, witha track recordof building successful AI solutions and productizing ML Models, Features Stores Solidtrack recordof over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; proven results in delivery on platform products. Masters / bachelor s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technicalexpertisein one or more of the above-mentioned areas or equivalent practical experience. Experience developing Gen AI applications/services usingPrompt Engineering, LLMs, and fine-tuning methodsfor sophisticated business use caseswithlarge amountsof unstructured data. Strong background in deep learning techniques, particularly in NLP and Vision Proficiencyin multiple Programming/scripting languages,i.e.Python, Java, Scala,SQL, NoSQL (like HBase, Redis, Aerospike) Strongproficiencyin machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models. Expertisein buildingMLpipelines with Big Data technologies such as Hadoop, Spark, HBase, Kafka. Good understanding of distributed systems, data streaming, complex event Processing, NoSQL solutions for creating and managing data integration pipelines for batch and Real Time data needs. Experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential. Preferred Prior experience in Content Understanding, enrichment, entity resolution or knowledge graph Strong background in MLOps and experimentation frameworks Extensive experience with concurrent, parallel, and distributed computing, including performance tuning and optimization for large-scale applications

Qualifications Masters / bachelor s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technicalexpertisein one or more of the above-mentioned areas or equivalent practical experience. Strong background in deep learning techniques, particularly in NLP and Vision Expertisein applying LLMs, prompt design, and fine-tuning methods Strongproficiencyin machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models. Expert in multiple Programming/scripting languages,i.e.,Python, Java, Scala, SQL, NoSQL (like HBase, Redis, Aerospike) Good understanding of distributed systems, data streaming, complex event Processing,NoSQLsolutions for creating and managing data integration pipelines for batch and Real Time data needs. Expertisein machine learning libraries/frameworks such as TensorFlow,PyTorch, scikit-learn,etc. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus Stay up to date with the latest advancements in AI/ML technology and industry trends andleveragethis knowledge to enhance the platforms capabilities Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Expertisein Big Data technologies such as Hadoop, Spark, HBase, Kafka. Preferred Prior experience in Content Understanding, enrichment, entity resolution or knowledge graph Experience developing Gen AI applications/services for sophisticated business use cases andlarge amountsof unstructured data. Strong background in MLOps and experimentation frameworks

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Responsibilities: Design and develop AI models and algorithms. Build and train ML systems. Process large datasets. Deploy models to production. Collaborate with teams to integrate AI solutions. Ensure model accuracy. Stay updated with AI trends. Health insurance Leave encashment Maternity leaves Paternity leaves Course reimbursements Capability building program Prevention of sexual harrassment policy

Design, develop, and maintain Conversational AI models including Chat BOTs. Develop robust unit and integration tests using testing frameworks/ manual to guarantee code quality and application stability. Expertly debug and troubleshoot complex application issues. Integrate Gen AI capabilities to enhance the product efficiency and effectiveness. Proven experience building Conversational AI models / Chat BOTs using Kore.ai platform. In depth understanding of Gen AI capabilities Proficiency in unit testing frameworks. Experience in Data Analytics and Python Exceptional problem solving and debugging skills. Excellent communication and collaboration skills. Experience in Agile Scrum practice. Experience in JIRA and Confluence Ability to work independently and manage multiple tasks effectively while contributing to a team environment.

Req ID: 327886 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a AI & LLM Engineer - Digital Engineering Sr. Engineer to join our team in Hyderabad, Telangana (IN-TG), India (IN). Software Engineer - LLM & Agentic AI Systems Design and build intelligent agents using LLMs that can autonomously complete tasks via planning, reasoning, and tool use. Develop backend services and APIs to support AI agent workflows and integrations. Implement planning frameworks (e.g., ReAct, AutoGPT, BabyAGI, LangGraph) and decision-making loops using LLMs. Build, test, and optimize LLM-based applications with tools like LangChain, LlamaIndex, or Semantic Kernel. Create and manage pipelines that connect LLMs to tools, APIs, and databases in real-time. Collaborate with ML/AI researchers, data engineers, and product teams to ship LLM-powered experiences. About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click . If you'd like more information on your EEO rights under the law, please click . For Pay Transparency information, please click.

What You'll Do We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will have a blend of technical skills in the fields of AI & Machine Learning especially with LLMs and a deep-seated understanding of software development practices where you'll work with a team to ensure our systems are scalable, performant and accurate. You will be reporting to Senior Manager, AI/ML. What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Inspire creativity by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration. Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful Bachelor's/Master's degree in computer science with 5+ years of industry experience in software development, along with experience building Machine Learning models and deploying them in production environments. Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. Work with technological innovations in AI & ML(esp. GenAI) Experience with design patterns and data structures. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, Grafana

Job Description- 5-8 years of strong hands-on experience in software development, with a focus on full stack development and an understanding of AI/ML or GenAI. -Experience on full stack implementation from frontend UI/UX to backend logic and infrastructure. -Design and develop responsive web applications using ReactJS and build robust backend services and APIs using Python. -Proficiency in Python, including experience with data processing, API integration, and automation scripting -Experience in working on Linux OS -Proven expertise in Cloud Infrastructure as Code using AWS CloudFormation, Terraform, or equivalent tooling in Azure/GCP -Deep understanding of Object-Oriented Programming (OOP) principles and applying them in scalable and maintainable system design -Demonstrated experience in end-to-end SDLC (Software Development Life Cycle): requirement gathering, design, development, testing, deployment, and support -Proficient in version control systems like Git and devops aware -Experience with using containerization technologies such as Docker, and orchestration using Kubernetes -Good to have handson experience with one of the following Generative AI concepts: -Working with Large Language Models (LLMs) such as GPT, LLaMA, Claude, etc. -Building intelligent systems using LangGraph, Agentic AI frameworks, or similar orchestration tools -Implementing Retrieval-Augmented Generation (RAG), prompt engineering, and knowledge augmentation techniques -Strong problem-solving and debugging skills, with an ability to write clean, efficient, and maintainable code -Excellent verbal and written communication skills, with the ability to collaborate effectively across technical and business teams -Personal GitHub project to prove the experience Must Have Skills: AI Fullstack Developer, Strong Python Scripting, ata processing, API integration, and automation scripting, Fullstack Development, RAG, LLM's, Deep Learning, Cloud Platform (AWS, Azure, GCP), ReactJS/ NodeJS, SDLC Lifecycle, OOP's Concepts. If interested in opportunity, please click on apply to procced further.