20 Rlhf Jobs

You will be joining a technology-driven publishing and legal-tech organization that is currently enhancing its capabilities through advanced AI initiatives. As an experienced AI Solution Architect, your role will involve leading the design, development, and deployment of transformative AI projects. You will work closely with a proficient internal team skilled in .NET, MERN, MEAN stacks, and recent chatbot development using OpenAI and LLaMA. Your responsibilities will include architecting, planning, and delivering enterprise-grade AI solutions utilizing Vector Databases like FAISS and Chroma, RAG Pipelines (Retrieval-Augmented Generation), and LLM techniques such as Pre-training, Fine-tuning, and RLHF (Reinforcement Learning with Human Feedback). You will lead AI solution design discussions, collaborate with engineering teams to integrate AI modules into systems, and guide junior AI engineers and developers on technical aspects. To excel in this role, you should hold a Bachelors or Masters in Computer Science, Engineering, AI/ML, or related fields and have at least 5 years of experience in software architecture with a focus on AI/ML system design and project delivery. Hands-on expertise in Vector Search Engines, LLM Tuning & Deployment, RAG systems, RLHF techniques, and working with multi-tech teams is essential. Strong command over architecture principles, scalability, microservices, API-based integration, and excellent team leadership skills are also required. It would be advantageous if you have experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, Azure/AWS AI services, exposure to data pipelines, MLOps, AI governance, familiarity with enterprise software lifecycle, and DevSecOps practices. Prior experience in delivering a production-grade AI/NLP project with measurable impact is a plus. Stay updated on emerging AI trends and assess their relevance to business objectives to drive AI adoption across products and internal processes.,

You will be joining a technology-driven publishing and legal-tech organization that is currently expanding its capabilities through advanced AI initiatives. With a strong internal team proficient in .NET, MERN, MEAN stacks, and recent chatbot development using OpenAI and LLaMA, we are seeking an experienced AI Solution Architect to lead the design, development, and deployment of transformative AI projects. As an AI Solution Architect, you will play a critical role in designing and delivering enterprise-grade AI solutions. Your responsibilities will include architecting, planning, and implementing AI solutions using Vector Databases, RAG Pipelines, and LLM techniques. You will lead AI solution design discussions, collaborate with engineering teams to integrate AI modules, evaluate AI frameworks, and mentor junior AI engineers and developers. To excel in this role, you should have a Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or related fields, along with at least 5 years of experience in software architecture with a focus on AI/ML system design and project delivery. Hands-on expertise in Vector Search Engines, LLM Tuning & Deployment, RAG systems, and RLHF techniques is essential. You should also have experience working with multi-tech teams, strong command over architecture principles, and excellent team leadership skills. Experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, and Azure/AWS AI services would be a plus. Exposure to data pipelines, MLOps, and AI governance, as well as familiarity with enterprise software lifecycle and DevSecOps practices, are also desirable. If you are passionate about AI technology, have a proven track record of delivering AI projects, and enjoy leading and mentoring technical teams, we encourage you to apply for this exciting opportunity to drive AI adoption across products and internal processes.,

The ideal candidate for this role should have a solid understanding of the technical aspects of Large Language Models (LLMs) and possess proficient skills in prompt engineering. You will be responsible for running tests, fine-tuning various LLM models and data to enhance model performance and output quality. Additionally, you will be required to explore cutting-edge AI/GenAI technology stacks under the guidance of the manager to enhance LLUMO's product offerings. A basic understanding of data engineering is also essential for this position. Your expertise should include a deep understanding of the architecture and functioning of LLMs such as GPT, LLAMA, BISON, among others. You should be familiar with application development frameworks like LangChain, LlamaIndex, and have knowledge of vector index and vector databases. A strong grasp of underlying architecture and algorithms like RLHF, transformers, attention mechanism, and DNNs is crucial. Proficiency in Python and frameworks like Hugging Face transformers, PyTorch, etc., is required. Prior experience in prompt engineering techniques to customize the behavior of LLMs for specific tasks is preferred. You should be skilled in the fine-tuning process to adapt models to particular domains or tasks. Knowledge of tools and techniques for interpreting the behavior of LLMs and proficiency in version control systems such as Git for tracking code and model configuration changes are necessary. Moreover, familiarity with ethical and legal considerations in language model development, including bias-hallucination mitigation, is essential. The qualifications for this position include a Bachelor's or advanced degree in Computer Science, Natural Language Processing (NLP), or a related field. This is a full-time job with a work schedule from Monday to Friday, and the work location is in-person. Job Type: Full-time Schedule: Monday to Friday Work Location: In person,

As a Senior Applied Researcher at Genloop, you will lead cutting-edge work in small language model (SLM) training, LLM customization, and domain adaptation. We believe that domain intelligence is crucial to bring GenAI into enterprise production, especially in cases where a 1-year employee outperforms a 1st-day hire significantly. Your responsibilities will include designing and conducting experiments, customizing LLMs for specific enterprise domains, evaluating model performance, collaborating with engineering and product teams, contributing to research documentation and open-source releases, and staying updated on LLM architectures and pretraining objectives. Additionally, you will mentor junior researchers and provide guidance to the broader team based on insights from the frontier. To qualify for this role, you should have at least 5 years of experience in ML research or applied deep learning, with a focus on NLP, foundation models, or multi-modal systems. A deep understanding of transformers, language modeling, and sequence generation is required, along with hands-on experience in pretraining, SFT, RLHF, and efficient fine-tuning methods. Strong publications or open-source contributions would be advantageous. Graduation from a Tier 1 institution or demonstrating exceptional skills are preferred. Genloop is a research-first AI company that specializes in building customized, continuously learning AI systems. Our team comprises researchers and engineers from prestigious institutions and tech companies, working on models with real-world, production-grade impact. In terms of compensation and benefits, we offer a competitive salary, meaningful startup equity, and industry-leading benefits. The exact compensation will be based on your experience, expertise, and location. Genloop is an Equal Opportunity Employer that values diversity and is dedicated to creating an inclusive and respectful workplace for all.,

As a Data Scientist at Objectways located in Chennai, you will have the opportunity to be part of a team that is driving AI innovation and solving real-world problems by leveraging cutting-edge machine learning and reasoning technologies. Our projects are ambitious and diverse, ranging from agent trajectory prediction to complex reasoning systems, multimodal intelligence, and preference-based learning. We are looking for a talented individual like you who is eager to explore the boundaries of applied AI. In this role, you will be responsible for designing and developing machine learning models for both structured and unstructured data. You will work on agent trajectory prediction, complex reasoning, preference ranking, and reinforcement learning. Additionally, you will handle multimodal datasets and develop reasoning pipelines across text, image, and audio modalities. Your responsibilities will also include validating and optimizing prompts for large language model performance and translating research into scalable, production-level implementations. Collaboration with cross-functional teams such as Engineering, Product, and Research is essential to ensure the success of our projects. To qualify for this position, you should have a minimum of 4 years of hands-on experience in Data Science or Machine Learning roles. Proficiency in Python, PyTorch/TensorFlow, scikit-learn, and ML lifecycle tools is required. You should also demonstrate expertise in at least one of the following areas: trajectory modeling, preference ranking, or multimodal systems. Experience with LLM prompt engineering, complex reasoning algorithms, graph-based methods, and causal inference is highly beneficial. Strong problem-solving, analytical thinking, and communication skills are essential for success in this role. Preferred skills for this position include familiarity with tools like LangChain, Hugging Face, or OpenAI APIs, exposure to RLHF (Reinforcement Learning from Human Feedback) or prompt-tuning, and experience with deploying ML models in production environments using technologies such as Docker and MLflow. By joining Objectways, you will have the opportunity to work on high-impact, next-generation AI challenges, collaborate with top talent from various domains, and enjoy a competitive salary with benefits and a learning budget.,

The Implementation Technical Architect role focuses on designing, developing, and deploying cutting-edge Generative AI (GenAI) solutions using the latest Large Language Models (LLMs) and frameworks. Your responsibilities include creating scalable and modular architecture for GenAI applications, leading Python development for GenAI applications, building tools for automated data curation, integrating solutions with cloud platforms like Azure, GCP, and AWS, applying advanced fine-tuning techniques to optimize LLM performance, establishing LLMOps pipelines, ensuring ethical AI practices, implementing Reinforcement Learning with Human Feedback and Retrieval-Augmented Generation techniques, collaborating with front-end developers, and more. Key Responsibilities: - Design and Architecture: Create scalable and modular architecture for GenAI applications using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Python Development: Lead the development of Python-based GenAI applications, ensuring high-quality, maintainable, and efficient code. - Data Curation Automation: Build tools and pipelines for automated data curation, preprocessing, and augmentation to support LLM training and fine-tuning. - Cloud Integration: Design and implement solutions leveraging Azure, GCP, and AWS LLM ecosystems, ensuring seamless integration with existing cloud infrastructure. - Fine-Tuning Expertise: Apply advanced fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLM performance for specific use cases. - LLMOps Implementation: Establish and manage LLMOps pipelines for continuous integration, deployment, and monitoring of LLM-based applications. - Responsible AI: Ensure ethical AI practices by implementing Responsible AI principles, including fairness, transparency, and accountability. - RLHF and RAG: Implement Reinforcement Learning with Human Feedback (RLHF) and Retrieval-Augmented Generation (RAG) techniques to enhance model performance. - Modular RAG Design: Develop and optimize Modular RAG architectures for complex GenAI applications. - Open Source Collaboration: Leverage Hugging Face and other open-source platforms for model development, fine-tuning, and deployment. - Front-End Integration: Collaborate with front-end developers to integrate GenAI capabilities into user-friendly interfaces. Required Skills: - Python Programming: Deep expertise in Python for building GenAI applications and automation tools. - LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data. - Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models. - Fine-tune SLM(Small Language Model) for domain specific data and use cases. - Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc. - Anti-hallucination and anti-gibberish tools such as Bleu etc. - Cloud Platforms: Extensive experience with Azure, GCP, and AWS LLM ecosystems and APIs. - Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. - LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management. - Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations. - RLHF and RAG: Advanced skills in Reinforcement Learning with Human Feedback and Retrieval-Augmented Generation. - Modular RAG: Deep understanding of Modular RAG architectures and their implementation. - Hugging Face: Proficiency in using Hugging Face and similar open-source platforms for model development. - Front-End Integration: Knowledge of front-end technologies to enable seamless integration of GenAI capabilities. - SDLC and DevSecOps: Strong understanding of secure software development lifecycle and DevSecOps practices for LLMs.,

Hiring a Python Code Reviewer for a 6-month remote contractual position The ideal candidate should have 4-8 years of experience in Python development, QA, or code review, with a strong grasp of Python syntax, edge cases, debugging, and testing The role involves reviewing annotator evaluations of AI-generated Python code to ensure quality, functional accuracy, and alignment with prompt instructions Experience with Docker, code execution tools, and structured QA workflows is mandatory Strong written communication skills and adherence to quality assurance guidelines (Project Atlas) are required Familiarity with LLM evaluation, RLHF pipelines, or annotation platforms is a plus Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

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

Soul AI is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. We are seeking a SME Mathematics (Freelancer) to join us and contribute to impactful AI training projects. If you have a deep understanding of mathematics and a passion for problem-solving, we want you to be part of our team!. Key Responsibilities:. Soul AI is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. Who you are & how you can contribute. We are seeking a Physics expert with a MSc degree. The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques. This fully remote position allows for flexible work hours while contributing to AIs advancement. What you will be doing. Annotate Physics-related data to improve AI comprehension. Provide feedback on AI-generated responses to ensure scientific accuracy. Assist in developing problem sets and solutions for AI training. Collaborate with AI researchers to refine AI capabilities in the field of Physics. Must Required Traits:. Strong academic background in Physics. Experience in Physics education, research, or content creation preferred. Familiarity with AI, machine learning, or data annotation is a plus. Excellent problem-solving and analytical skills.

Who you are & how you can contribute. We are seeking a Chemistry expert with a PhD degree. The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques. This fully remote position allows for flexible work hours while contributing to AIs advancement. What you will be doing. Annotate Chemistry-related data to improve AI comprehension. Provide feedback on AI-generated responses to ensure scientific accuracy. Assist in developing problem sets and solutions for AI training. Collaborate with AI researchers to refine AI capabilities in the field of Chemistry. Must Required Traits: Strong academic background in Chemistry. Experience in Chemistry education, research, or content creation preferred. Familiarity with AI, machine learning, or data annotation is a plus. Excellent problem-solving and analytical skills.

Job Summary Who you are & how you can contribute We are seeking a Physics expert with a MSc degree The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques This fully remote position allows for flexible work hours while contributing to AIs advancement What you will be doing Annotate Physics-related data to improve AI comprehension Provide feedback on AI-generated responses to ensure scientific accuracy Assist in developing problem sets and solutions for AI training Collaborate with AI researchers to refine AI capabilities in the field of Physics Must Required Traits: Strong academic background in Physics Experience in Physics education, research, or content creation preferred Familiarity with AI, machine learning, or data annotation is a plus Excellent problem-solving and analytical skills

Job Summary Who you are & how you can contribute We are seeking a Physics expert with a MSc degree The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques This fully remote position allows for flexible work hours while contributing to AIs advancement What you will be doing Annotate Physics-related data to improve AI comprehension Provide feedback on AI-generated responses to ensure scientific accuracy Assist in developing problem sets and solutions for AI training Collaborate with AI researchers to refine AI capabilities in the field of Physics Must Required Traits: Strong academic background in Physics Experience in Physics education, research, or content creation preferred Familiarity with AI, machine learning, or data annotation is a plus Excellent problem-solving and analytical skills

What you will be doing: Annotate Biology-related data to improve AI comprehension. Provide feedback on AI-generated responses to ensure scientific accuracy. Assist in developing problem sets and solutions for AI training. Collaborate with AI researchers to refine AI capabilities in the field of Biology. Must Required Traits: Strong academic background in Biology. Experience in Biology education, research, or content creation preferred. Familiarity with AI, machine learning, or data annotation is a plus. Excellent problem-solving and analytical skills.

We are seeking an experienced Physics SME to create high-quality educational content. This is a remote, flexible opportunity to work on cutting-edge AI projects by applying your domain expertise to refine AI's understanding and performance. Key Responsibilities Annotate and evaluate AI-generated Physics content. Ensure accurate, age-appropriate explanations of topics such as Mechanics, Electromagnetism, Optics, and Thermodynamics. Design prompts and review AI responses for clarity, engagement, and conceptual depth. Provide feedback to improve AI reasoning and instructional quality. Required Qualifications PhD in Physics, Education, or a related field. Strong knowledge of Physics. Ability to explain complex Physics concepts clearly and engagingly. Experience in content creation or teaching Physics is a plus. Familiarity with online teaching tools and educational platforms.

Soul AI is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. We are seeking a SME Mathematics (Freelancer) to join us and contribute to impactful AI training projects. If you have a deep understanding of mathematics and a passion for problem-solving, we want you to be part of our team!. Key Responsibilities:. Soul AI is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. Who you are & how you can contribute. We are seeking a Physics expert with a MSc degree. The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques. This fully remote position allows for flexible work hours while contributing to AIs advancement. What you will be doing. Annotate Physics-related data to improve AI comprehension. Provide feedback on AI-generated responses to ensure scientific accuracy. Assist in developing problem sets and solutions for AI training. Collaborate with AI researchers to refine AI capabilities in the field of Physics. Must Required Traits:. Strong academic background in Physics. Experience in Physics education, research, or content creation preferred. Familiarity with AI, machine learning, or data annotation is a plus. Excellent problem-solving and analytical skills.

We are seeking a Biology expert with an BSc degree The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques This fully remote position allows for flexible work hours while contributing to AIs advancement What you will be doing Annotate Biology-related data to improve AI comprehension Provide feedback on AI-generated responses to ensure scientific accuracy Assist in developing problem sets and solutions for AI training Collaborate with AI researchers to refine AI capabilities in the field of Biology Must Required Traits: Strong academic background in Biology Experience in Biology education, research, or content creation preferred Familiarity with AI, machine learning, or data annotation is a plus Excellent problem-solving and analytical skills

We are seeking a Biology expert with an BSc degree The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques This fully remote position allows for flexible work hours while contributing to AIs advancement What you will be doing Annotate Biology-related data to improve AI comprehension Provide feedback on AI-generated responses to ensure scientific accuracy Assist in developing problem sets and solutions for AI training Collaborate with AI researchers to refine AI capabilities in the field of Biology Must Required Traits: Strong academic background in Biology Experience in Biology education, research, or content creation preferred Familiarity with AI, machine learning, or data annotation is a plus Excellent problem-solving and analytical skills

We are seeking a Biology expert with an BSc degree The role involves working on data annotation and model refinement for AI through RLHF and SFT techniques This fully remote position allows for flexible work hours while contributing to AIs advancement What you will be doing Annotate Biology-related data to improve AI comprehension Provide feedback on AI-generated responses to ensure scientific accuracy Assist in developing problem sets and solutions for AI training Collaborate with AI researchers to refine AI capabilities in the field of Biology Must Required Traits: Strong academic background in Biology Experience in Biology education, research, or content creation preferred Familiarity with AI, machine learning, or data annotation is a plus Excellent problem-solving and analytical skills

Key Responsibilities: Research & Innovation: Conduct applied research in generative AI, foundation models, NLP, computer vision, and multimodal AI. Stay abreast of the latest publications and open-source advancements. Model Development: Fine-tune, evaluate, and optimize large language models (LLMs), transformers, and other generative models for specific business and product use cases. Prototyping & Experimentation: Build proof-of-concepts and experimental systems that demonstrate the potential of GenAI across domains such as content generation, summarization, synthetic data, agent systems, etc. Data & Evaluation Pipelines: Design robust data pipelines, evaluation metrics, and benchmarking systems to validate model performance, safety, and bias. Collaboration: Work with cross-functional teams including product managers, ML engineers, and data scientists to translate research into production-grade systems. Open Source & IP Contribution: Publish findings in peer-reviewed venues, contribute to open-source projects, or generate intellectual property relevant to the business. Required Qualifications: 57 years of experience in machine learning or applied AI roles, with at least 23 years working on generative models or related research. Strong foundation in deep learning frameworks such as PyTorch, TensorFlow, or JAX. Experience with LLMs (e.g., GPT, LLaMA, Claude), diffusion models, or vision-language models. Proficient in Python and ML tools/libraries such as Hugging Face Transformers, LangChain, or similar. Understanding of responsible AI practices, bias mitigation, and model explainability. Master's or PhD in Computer Science, Machine Learning, Mathematics, or related fields. Preferred Qualifications: Experience with open-source LLMs or fine-tuning techniques like LoRA, PEFT, RLHF, etc. Knowledge of MLOps practices and deployment of models in production (e.g., via Kubernetes, Ray, Triton).

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.