14 Model Finetuning Jobs

As an AI/ML Engineer at our client's dynamic, venture-backed startup in Bangalore, you will be revolutionizing semiconductor design with cutting-edge AI tools. Founded by serial entrepreneurs with deep industry expertise and over 75 patents, our client empowers chip designers to streamline workflows, boost productivity, and accelerate innovation. Join our world-class team to build intelligent assistants that are truly game-changing for the industry. To excel in this role, you must possess a strong theoretical understanding and practical application of deep learning principles. Proficiency in developing and debugging robust machine learning models using Python and leading ML libraries such as PyTorch and TensorFlow is crucial. Expertise in Graph Neural Networks will give you a significant edge in tackling complex semiconductor challenges. Additionally, demonstrated expertise in Large Language Models, including prompt engineering, supervised fine-tuning, and architecting agentic workflows, is highly valued. You should have at least 4 years of hands-on experience in the field, coupled with a degree in Mathematics, Computer Science, or Electronics. Your key responsibilities will include preparing high-quality datasets from various unstructured data sources, developing intricate knowledge graphs, applying advanced data augmentation techniques, developing intelligent agentic workflows around Large Language Models, crafting evaluation frameworks for LLMs, and deploying cutting-edge models in on-premise environments. Desired skills and experience for this role include proficiency in PyTorch, NLP, prompt engineering, model fine-tuning, Python, Graph Neural Networks, Knowledge Graph, and RAG (Retrieval-Augmented Generation). Joining our client's team offers you the opportunity to define the future of semiconductor design. If you are a passionate Deep Learning enthusiast with a flair for system architecture, eager to tackle complex challenges and make a mark on the industry, we invite you to apply now. This is an on-site position located in Bengaluru. If you are ready to build the future, not just maintain it, please send your resume to rekha.cxc@careerxperts.com.,

You should have a minimum of 2 years of relevant experience in Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. Additionally, you should have exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. Moreover, hands-on experience with modality-specific encoder models for multi-modal AI applications and proficiency in model fine-tuning, prompt engineering, and using both open-source and proprietary LLMs is required. Experience with model quantization, optimization, and conversion techniques for efficient deployment, including edge devices is also essential. You should possess a deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. Strong MLOps knowledge is required with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions is a must. Familiarity with data preprocessing, standardization, and knowledge graphs is considered a nice-to-have skill. Furthermore, you should have a strong analytical mindset with a passion for building robust, scalable AI solutions and be skilled in Python, writing clean, modular, and efficient code. Proficiency in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic is also required. Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search is essential. Exposure to Neo4j and graph databases for relationship-driven insights is a plus. Hands-on experience with Docker and containerization to build scalable, reproducible, and portable AI services is expected. Being up-to-date with the latest trends in GenAI, LLMs, Agentic AI, and deployment strategies is crucial. Strong communication and collaboration skills are necessary, as you should be able to contribute in cross-functional and fast-paced environments. Bonus skills include experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing, as well as working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar technologies. This is a full-time job with a day shift schedule. The expected start date is 23/06/2025. The work location is in person.,

As a Fullstack Python Developer specializing in FastAPI, React, and Generative AI, you will play a crucial role in developing scalable web applications, intelligent APIs, and AI-powered user experiences. Your responsibilities will span from backend development using Python and FastAPI to frontend development with React. Additionally, you will integrate Generative AI models to enhance the functionality of the applications you build. Your key responsibilities will include developing and maintaining RESTful APIs with FastAPI, implementing microservices architecture, and integrating GenAI models such as OpenAI, Hugging Face, and Stability AI. On the frontend side, you will work on creating responsive and dynamic user interfaces using React or Next.js, ensuring seamless integration with backend services and GenAI outputs. In terms of Generative AI integration, you will implement features like text summarization, intelligent search, and image generation. You will also work with vector databases like Pinecone and Qdrant, optimizing prompt engineering and model interaction for performance and accuracy. Furthermore, you will be involved in DevOps and Infrastructure tasks, including containerizing applications using Docker and deploying them via Kubernetes or cloud platforms. You will also set up CI/CD pipelines and monitor system performance and reliability. To excel in this role, you should have at least 4 years of experience in fullstack development and a strong proficiency in Python, FastAPI, and ReactJS. Experience with GenAI tools and APIs such as LangChain, Hugging Face, and OpenAI is essential. Familiarity with technologies like Redis, RabbitMQ, Docker, and cloud services (AWS/GCP) is also required. An understanding of RESTful APIs, async processing, and vector search will be beneficial. Additionally, bonus skills include experience with multimodal GenAI (text, image, audio), knowledge of prompt engineering and model fine-tuning, and contributions to open-source AI or fullstack projects.,

You will be working as a Machine Learning Engineer in an in-office setting in Hyderabad. Your primary focus will be on utilizing AI/ML techniques, specifically in computer vision applications. Your responsibilities will include designing, building, and fine-tuning machine learning models for tasks like object detection, segmentation, and image classification. As a Machine Learning Engineer, you will leverage pre-trained models and implement fine-tuning to customize them for specific use cases. It will be crucial for you to optimize model performance by incorporating cutting-edge techniques in transfer learning, regularization, and hyperparameter tuning. Collaboration with data scientists, engineers, and product teams is essential to deliver AI solutions that align with business requirements. Your role will involve developing scalable solutions and deployment pipelines to operationalize machine learning models effectively. You will need to prioritize model efficiency, ensuring high speed and low latency in production environments. Staying updated on the latest trends and technologies in AI, machine learning, and computer vision will be key in enhancing existing solutions. Additionally, you will conduct thorough evaluations of models using relevant metrics and implement strategies for performance enhancement. Troubleshooting and resolving model-related issues in production environments will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's, Master's, or PhD in Computer Science and possess at least 3 years of experience in machine learning or deep learning, focusing on computer vision. Expertise in model fine-tuning, transfer learning, and working with pre-trained models like ResNet, VGG, and EfficientNet is required. Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Keras, along with a deep understanding of deep learning architectures, is essential. Familiarity with vision-specific tasks, data preprocessing, augmentation, and labeling techniques for vision tasks, as well as proficiency in programming languages like Python, C++, or similar, are necessary. A strong grasp of model evaluation techniques and metrics for computer vision tasks and experience with cloud platforms and containerization technologies will be advantageous.,

You should have 6-10+ years of experience in AI/ML development, including at least 3 years of hands-on experience in Generative AI, RAG frameworks, and Agentic AI systems. As a Generative AI Engineer, you will be responsible for designing, developing, and optimizing RAG pipelines using frameworks such as LangChain, LlamaIndex, or custom-built stacks. You will also implement Agentic AI architectures involving task-based agents, stateful memory, planning-execution workflows, and tool augmentation. Additionally, you will perform model fine-tuning, embedding generation, and evaluation of LLM outputs while incorporating human and automated feedback loops. Building and enforcing guardrails to ensure safe, compliant, and robust model behavior will be a crucial part of your role, including prompt validation, output moderation, and access controls. Collaboration with cross-functional teams to deploy solutions in cloud-native environments such as Azure OpenAI, AWS Bedrock, or Google Vertex AI will also be expected. Furthermore, you will contribute to system observability via dashboards and logging, as well as support post-deployment model monitoring and optimization. To excel in this role, you must have proven production experience with RAG frameworks like LangChain, LlamaIndex, or custom-built solutions. A solid understanding of Agentic AI design patterns, strong expertise in LLM fine-tuning, vector embeddings, evaluation strategies, and feedback integration are essential. Experience with implementing AI guardrails, proficiency in Python, LLM APIs (OpenAI, Anthropic, Cohere, etc.), and vector database integration are also required. Familiarity with CI/CD pipelines, API integrations, and cloud-native deployment patterns is a plus. Preferred qualifications include experience working on AI projects in regulated environments (Banking domain), hands-on experience with cloud AI platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI, knowledge of prompt engineering, RLHF, and LLM observability frameworks, as well as experience building or leveraging internal LLM evaluation harnesses, agent orchestration layers, or compliance dashboards.,

As a Prompt Engineer in the Artificial Intelligence/R&D department, you will play a vital role in building, optimizing, and testing natural language prompts to enhance the performance of large language models like OpenAI GPT, Claude, and Gemini. Your primary responsibilities will involve designing, writing, and optimizing natural language prompts to address specific business or product challenges. Working alongside data scientists, product managers, and engineering teams, you will contribute to the development of high-quality AI prompt systems for real-world applications. Your role will require you to analyze and test the impact of different prompts on model output quality, collaborating closely with product and development teams to create deployable prompt templates and interface logic. Additionally, you will be involved in establishing prompt libraries and prompt engineering frameworks to enhance prompt reusability and scalability. Staying updated on the latest prompt engineering technologies and research papers will be crucial, as you transform these insights into practical applications. To excel in this role, you must demonstrate proficiency in utilizing mainstream large-scale language models such as GPT-4, Claude, or Gemini. Strong language expression and logical thinking skills, along with expertise in prompt tuning, few-shot learning, and chain-of-thought prompt engineering methods, are essential. A bachelor's degree in a relevant field (computer science, linguistics, cognitive science) is required, with a preference for candidates with strong English reading abilities to understand model documents and research papers. Candidates with experience in actual Large Language Model (LLM) application projects, mastery of Python programming for rapid prototyping, and familiarity with dialogue systems, search engines, knowledge graphs, and RAG technologies will be given bonus points. Understanding model fine-tuning, LoRA, and system prompt structure, as well as familiarity with tool chains like LangChain, LlamaIndex, and OpenAI Function Calling, will be advantageous. In return, we offer a competitive salary and bonus system, the chance to work with cutting-edge AI technology, flexible working hours, and remote work options. Join our team of technology enthusiasts and innovators to embark on a rewarding career journey.,

As a member of the Classical ML+NLP+Gen AI - L4 team at Tredence, you will be involved in tasks such as Model Fine-tuning, Model Pre-training, Named Entity Recognition, Prompt Engineering, Pyspark, Python, Regular expressions, SQL, Supervised ML, Tokenization, Transformer Models, Transformers, Unstructured Data Pre-processing, and Unsupervised ML. Tredence, founded in 2013, is a company dedicated to transforming data into actionable insights. With a focus on helping over 50 Fortune 500 clients succeed in their industries, we operate globally with our headquarters in San Jose and a presence in 5 countries. Our goal is to be the world's most indispensable analytics partner by combining deep domain expertise with advanced AI and data science to deliver exceptional business value. We welcome you to be a part of our team and contribute to our innovative journey.,

As a Senior ML/AI Engineer at our Technology Innovation Lab, you will be a key member of a cross-disciplinary team dedicated to advancing AI and intelligent automation at HERE. Your primary responsibility will be to develop cutting-edge machine learning systems that leverage Agentic AI, Generative AI, and foundational ML techniques to drive the next generation of applications. Collaborating closely with technical leads, researchers, and engineers, you will prototype solutions to address real-world spatial, operational, and knowledge-driven challenges. Your role will involve architecting and implementing AI-first systems using technologies such as Large Language Models (LLMs), Autonomous Multi-Agent Architectures, and Classical ML models like regression, clustering, XGBoost, SVM, and tree-based learners. Leading the development of Agentic AI solutions will be a core aspect of your role, encompassing tasks such as orchestration, memory/context management, tool invocation, and human-agent collaboration. You will also be responsible for designing and delivering end-to-end Generative AI applications for various purposes including text generation, summarization, code synthesis, image generation, and multi-modal interfaces. Your expertise in deep learning techniques, including CNNs, RNNs (LSTM, GRU), GANs, Diffusion Models, Transformers, and Graph Neural Networks, will be crucial for tackling real-world tasks in vision, language, and planning. You will collaborate across teams to translate domain-specific problems into scalable, explainable, and production-ready AI solutions while incorporating responsible AI principles. Staying at the forefront of AI research will be essential, as you evaluate and implement emerging LLM models, agentic frameworks, and open-source innovations to ensure technical currency in this rapidly evolving field. You will also design and lead experiments across advanced AI/ML areas, encompassing computer vision, NLP, LLMs, and emerging domains like quantum computing, distributed computing, 3D modeling, AR/VR, and LiDAR/drone data processing. Writing efficient, production-quality code using Python and leveraging frameworks like PyTorch, TensorFlow, and Spark for large-scale ML training and inference will be part of your daily tasks. Defining and tracking KPIs at both individual and business unit levels, in collaboration with your manager, will ensure that your work drives impactful innovation. Supporting and mentoring engineers and data scientists in best practices related to prompt design, agent workflows, evaluation frameworks, and research translation will also be part of your responsibilities. Additionally, contributing to HERE's innovation footprint through patents, internal IP development, and peer-reviewed publications will be encouraged. To qualify for this role, you should hold a Master's degree or Ph.D. in Computer Science, AI/ML, Mathematics, or a related field. Candidates with a Master's degree should have 5-7 years of experience, while Ph.D. holders may have 3-5 years of relevant experience. A strong understanding of ML fundamentals, hands-on experience with deep learning architectures, proficiency in Python, and familiarity with ML frameworks are essential qualifications. Curiosity and exposure to adjacent technologies like TinyML, Quantum Computing, or 3D modeling/AR will be considered advantageous. At HERE Technologies, we are a location data and technology platform company dedicated to empowering our customers and making a positive impact on people's lives. If you are passionate about driving innovation and creating positive change in an open world, we invite you to join us on this exciting journey.,

The position of Gen AI / AI Engineer (Mid-Level) in Hyderabad requires a candidate with at least 2 years of experience in developing and deploying AI/ML solutions, focusing particularly on Generative AI and RAG (Retrieval-Augmented Generation) architectures. As an AI Engineer, you will be involved in working with cutting-edge models, fine-tuning, and integrating systems to create scalable AI products. Your responsibilities will include fine-tuning and optimizing Large Language Models (LLMs) and generative models for both text and image data. You will also be responsible for designing and implementing RAG pipelines that incorporate knowledge bases, developing APIs, microservices, and scalable AI pipelines, collaborating with MLOps teams for production deployment, and staying updated on the latest AI trends to apply innovative techniques effectively. The ideal candidate should possess expertise in Python programming language, PyTorch or TensorFlow frameworks, Generative AI tools such as OpenAI, Anthropic, LLaMA, RAG architecture, Natural Language Processing (NLP), Computer Vision, API development, MLOps practices, and experience working with Cloud Platforms like AWS, Azure, or GCP. Qualifications for this role include a Bachelor's degree in Computer Science or a related field, a minimum of 2 years of experience in AI/ML with a focus on GenAI and RAG, and hands-on experience in deploying models at a production level. If you are enthusiastic about contributing to the development of next-generation AI solutions, we encourage you to apply for this exciting opportunity.,

You are an experienced AI/ML Engineer with a solid foundation in Machine learning, Artificial Intelligence, and at least one year of hands-on experience in Generative AI. You are proficient in Python, LLM Models, and emerging techniques such as Retrieval-Augmented Generation (RAG), model fine-tuning, and agentic AI systems. Your responsibilities will include designing, developing, and deploying AI/ML solutions with an emphasis on generative models and LLMs. You will implement and optimize RAG pipelines for knowledge-aware AI systems, fine-tune and customize models for specific domains or applications, and build and manage agentic AI systems capable of autonomous planning and decision-making. Collaboration with cross-functional teams to identify use cases and deliver scalable AI-powered features is essential. You will stay up to date with the latest developments in AI/ML and contribute to internal knowledge sharing. Required qualifications include 3+ years of experience in AI/ML development, a minimum of 1 year of hands-on experience in Generative AI projects, proficiency in Python and common ML libraries, a strong understanding of Large Language Models (LLMs) and transformer architectures, experience with RAG pipelines, and hands-on experience with model fine-tuning using LoRA, PEFT, or Hugging Face Transformers. Additionally, experience developing agentic AI systems and working with cloud platforms is necessary. You will work with frameworks & libraries such as LangChain, LlamaIndex, AutoGen, PyTorch, and TensorFlow, model providers like OpenAI, Anthropic, Llama, Mistral, vector stores such as FAISS, Pinecone, Milvus, and APIs & Services like REST, GraphQL. Experience with DevOps & Infra tools like Docker, AWS/GCP/Azure will be beneficial for this role.,

As a Python Developer within our Information Technology department, your primary responsibility will be to leverage your expertise in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI. We are seeking a candidate who possesses hands-on experience with GPT-4, transformer models, and deep learning frameworks, along with a profound comprehension of model fine-tuning, deployment, and inference. Your key responsibilities will include designing, developing, and maintaining Python applications that are specifically tailored towards AI/ML and generative AI. You will also be involved in building and refining transformer-based models such as GPT, BERT, and T5 for various NLP and generative tasks. Working with extensive datasets for training and evaluation purposes will be a crucial aspect of your role. Moreover, you will be tasked with implementing model inference pipelines and scalable APIs utilizing FastAPI, Flask, or similar technologies. Collaborating closely with data scientists and ML engineers will be essential in creating end-to-end AI solutions. Staying updated with the latest research and advancements in the realms of generative AI and ML is imperative for this position. From a technical standpoint, you should demonstrate a strong proficiency in Python and its relevant libraries like NumPy, Pandas, and Scikit-learn. With at least 7+ years of experience in AI/ML development, hands-on familiarity with transformer-based models, particularly GPT-4, LLMs, or diffusion models, is required. Experience with frameworks like Hugging Face Transformers, OpenAI API, TensorFlow, PyTorch, or JAX is highly desirable. Additionally, expertise in deploying models using Docker, Kubernetes, or cloud platforms like AWS, GCP, or Azure will be advantageous. Having a knack for problem-solving and algorithmic thinking is crucial for this role. Familiarity with prompt engineering, fine-tuning, and reinforcement learning with human feedback (RLHF) would be a valuable asset. Any contributions to open-source AI/ML projects, experience with vector databases, building AI chatbots, copilots, or creative content generators, and knowledge of MLOps and model monitoring will be considered as added advantages. In terms of educational qualifications, a Bachelor's degree in Science (B.Sc), Technology (B.Tech), or Computer Applications (BCA) is required. A Master's degree in Science (M.Sc), Technology (M.Tech), or Computer Applications (MCA) would be an added benefit for this role.,

You are an experienced AI/ML Engineer with a solid foundation in Machine Learning and Artificial Intelligence, and a minimum of one year of hands-on experience in Generative AI. Your expertise includes proficiency in Python, LLM Models, and emerging techniques such as Retrieval-Augmented Generation (RAG), model fine-tuning, and agentic AI systems. Your key responsibilities will involve designing, developing, and deploying AI/ML solutions focusing on generative models and LLMs. You will be required to implement and optimize RAG pipelines for knowledge-aware AI systems, fine-tune and customize models for specific domains, and build and manage agentic AI systems capable of autonomous planning and decision-making. Collaborating closely with cross-functional teams, you will identify use cases and deliver scalable AI-powered features. It is essential to stay updated with the latest AI/ML developments and contribute to internal knowledge sharing. To qualify for this role, you must have a minimum of 3 years of experience in AI/ML development, with at least one year of hands-on experience in Generative AI projects. Proficiency in Python and common ML libraries like PyTorch and scikit-learn is required. A strong understanding of Large Language Models (LLMs) and transformer architectures is essential. Experience in building RAG pipelines, integrating vector search systems, and model fine-tuning using tools like LoRA, PEFT, or Hugging Face Transformers is expected. Familiarity with developing agentic AI systems using frameworks such as LangChain, AutoGen, or custom orchestration logic is preferred. Additionally, experience working with cloud platforms is beneficial. You will work with frameworks and libraries including LangChain, LlamaIndex, AutoGen, PyTorch, and TensorFlow. Model providers you will engage with are OpenAI, Anthropic, Llama, and Mistral. Your expertise will also involve working with vector stores like FAISS, Pinecone, and Milvus, along with APIs & Services such as REST and GraphQL. In terms of DevOps & Infrastructure, you will utilize tools like Docker, AWS/GCP/Azure. Join us in this dynamic role where you will contribute to cutting-edge AI/ML projects and make a significant impact in the field of Artificial Intelligence.,

The company is seeking a Gen AI / AI Engineer with at least 2 years of experience in the field of AI/ML solutions, specifically focusing on Generative AI and RAG (Retrieval-Augmented Generation) architectures. The role involves working on cutting-edge models, fine-tuning, and integrating systems to develop scalable AI products. Responsibilities include fine-tuning and optimizing Large Language Models (LLMs) and generative models for text and image, designing and implementing RAG pipelines with knowledge bases, developing APIs, microservices, and scalable AI pipelines, collaborating with MLOps teams for production deployment, and staying updated on the latest AI trends to apply innovative techniques. The ideal candidate should possess skills in Python, PyTorch/TensorFlow, Generative AI (OpenAI, Anthropic, LLaMA), RAG architecture, Natural Language Processing (NLP), Computer Vision, API development, MLOps, and have experience working with Cloud Platforms such as AWS/Azure/GCP. Qualifications include a Bachelors degree in Computer Science or a related field, at least 2 years of experience in AI/ML with a focus on GenAI & RAG, and hands-on experience with production-grade model deployment. If you are enthusiastic about contributing to the development of next-generation AI solutions, we encourage you to apply for this exciting opportunity now!,

Company Name: Karini AI Job Title: Generative AI Engineer Location: Wakad, Pune (Onsite) Employment Type: Full-time Job Overview: Karini AI is looking for a highly motivated and skilled Generative AI Engineer to join our AI team. The ideal candidate should have expertise in Large Language Models (LLMs), Machine Learning (ML), and Deep Learning . We are looking for problem solvers, collaborative team players, and passionate individuals eager to work on cutting-edge AI technologies. If you aspire to be part of an innovative team and accelerate your career in AI, this is the perfect opportunity for you! Roles & Responsibilities: Collaborate with researchers, engineers, and domain experts to design, develop, and optimize Agentic AI applications . Fine-tune LLMs on large-scale datasets to enhance performance and accuracy. Develop compelling demos and lead proof-of-concept (PoC) projects. Stay updated with the latest research advancements in Generative AI and implement best practices. Deploy large-scale machine learning models in cloud-based environments. Mandatory Technical Skills: Hands-on experience in Generative AI and Deep Learning . Advanced knowledge of prompt engineering . Strong experience in PyTorch and working with GPUs . Proficiency in Python (Intermediate to Advanced level). Understanding of model fine-tuning and distributed computing in the cloud. Eligibility Criteria: Bachelors degree in Computer Science, AI, or a related field (4-year program). Masters degree in Artificial Intelligence or a related domain (preferred). Proven experience working as an AI Engineer with a strong foundation in Generative AI . Proficiency in deep learning frameworks and NLP techniques. Experience with cloud-based infrastructure for deploying machine learning models. Key Skills: Generative AI, Deep Learning, Machine Learning, Natural Language Processing (NLP), PyTorch, Python, Cloud Computing, LLM Fine-Tuning, Agentic AI, Lang graph.