1071 Llm Jobs - Page 36

Key Responsibilities: Design, develop, and train deep learning models for structured and unstructured data. Fine-tune pre-trained large language models (e.g., LLaMA, Mistral, Falcon, GPT-based models) for custom use cases. Evaluate model performance using standard metrics and improve based on experimentation. Build and maintain scalable training pipelines and inference systems. Collaborate with product and research teams to convert business requirements into technical solutions. Perform data preprocessing, augmentation, and annotation where needed. Optimize model inference speed and resource efficiency (e.g., quantization, pruning). Keep up with the latest research in ML/DL and apply relevant techniques to real-world problems. Required Qualifications: B.Tech / M.Tech / MS in Computer Science, Electrical Engineering, or related field. 23 years of hands-on experience in machine learning and deep learning. Strong knowledge of Python and frameworks such as PyTorch or TensorFlow. Proven experience training deep neural networks from scratch or via transfer learning. Exposure to LLMs – fine-tuning, prompt engineering, or training smaller transformer models. Familiarity with deployment of models using FastAPI, Flask, or similar. Preferred Qualifications: Experience with Hugging Face Transformers, LangChain, or similar frameworks. Knowledge of distributed training and GPU acceleration. Understanding of vector databases and RAG (retrieval-augmented generation) systems. Basic understanding of MLOps tools like Docker, Kubernetes, and CI/CD for ML workflows. Familiarity with common NLP tasks: text classification, summarization, NER, etc. What We Offer: A fast-paced, collaborative, and intellectually challenging environment. Opportunity to work on cutting-edge AI products and infrastructure. Flexible work options and a strong focus on work-life balance. Competitive compensation and equity options (if applicable).

Job Title: Technical Architect Generative AI Experience: 1418 Years Location: Noida Employment Type: Full-Time Job Summary: We are looking for a hands-on Technical Architect Generative AI to lead the design and implementation of AI-driven solutions across cloud-native environments. This role requires deep expertise in GenAI models, LLMs, Python, .NET Core, and Azure. The ideal candidate will actively contribute to coding, solution architecture, PoCs, and guide teams in applying GenAI to real-world business scenarios. Key Responsibilities: AI & Application Development Design and implement GenAI use cases (e.g., document summarization, conversational agents, RAG pipelines). Build and integrate LLMs using Python and Azure AI services. Develop scalable backend services with .NET Core Web APIs . Create modern frontends using Angular (13+) or React . Build PoCs and AI accelerators for enterprise-grade use cases. Architecture & System Design Architect and lead implementation of GenAI/LLM-based solutions on Azure . Build event-driven systems using Kafka, Azure Event Grid , or similar. Drive adoption of cloud-native patterns , security guidelines, and DevOps practices. Enforce code quality (SonarQube), security (Guiderails), and CI/CD pipelines. Stakeholder Collaboration Partner with product owners and business teams to translate workflows into GenAI-driven applications. Collaborate with other architects to define the AI/ML roadmap. Present architectural solutions and ROI-focused GenAI use cases to stakeholders. Leadership & Mentoring Conduct code reviews, performance tuning, and technical troubleshooting. Mentor developers on Python, .NET, LLM integration, and AI solution patterns. Contribute to knowledge sharing and technical upskilling across teams. Must-Have Skills: Programming & Frameworks Python : LLM integration, agentic frameworks, prompt engineering .NET Core : Web API, Entity Framework Angular 13+ / React , TypeScript Cloud & DevOps Azure AI Services : Cognitive Services, AI Builder, OpenAI/Foundry, Logic Apps Azure DevOps : CI/CD, Infrastructure-as-Code (ARM/Bicep) Event-driven architectures using Kafka/Event Grid AI/ML Expertise Generative AI, LLM fine-tuning, prompt design, RAG pipelines MLOps and integration of models in production environments Familiarity with tools like GitHub Copilot Qualifications: 1418 years of overall experience in software architecture and development At least 5+ years in AI/ML and cloud-native solutioning Bachelor's or Master's degree in Computer Science, Engineering, or related field Preferred: Azure Solutions Architect Expert or similar certifications Proven experience in enterprise-scale AI implementations (GitHub/GitLab links are a plus) Soft Skills: Strong communicator with ability to present technical ideas to stakeholders Team leadership and Agile methodology experience Innovation mindset and problem-solving orientation Reach Out: 9045052073

Role & responsibilities Hands-on programming and capabilities in Python, Java, R, or SCALA Experience in Enterprise applications development (Java, . Net) Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc. ) Strong hands-on experience with statistical packages and ML libraries (e. g. R, Python scikit learn, Spark MLlib, etc. ) Experience in effective data exploration and visualization (e. g. Excel, Power BI, Tableau, Qlik, etc. ) Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc. ) Hands on experience in RDBMS, NoSQL, big data stores like: Elastic, Cassandra, Hbase, Hive, HDFS Experience with open source software. Additional Requirements Defining, designing and delivering ML patterns operable in native and hybrid cloud architectures. Research, analyze, recommend and select technical approaches to address challenging development and data integration problems related to ML Model training and deployment in Enterprise Applications. Perform research activities to identify emerging technologies and trends that may affect the Data Science/ ML life-cycle management in enterprise application portfolio Basic knowledge in LLM butAI, NLP and deep learning should be strong Good with Associate architect or solution architect but no for Technical Lead. Hands on experience on Docker. Building docker images with a model and all its dependent packages into the image. Excellent problem-solving skills and ability to break down complexity. Ability to see multiple solutions to problems and choose the right one for the situation. Excellent written and oral communication skills. Demonstrated technical expertise around architecting solutions aroundAI, ML, deep learning and related technologies. DevelopingAI/ML models in real-world environments and integratingAI/ML using Cloud native or hybrid technologies into large-scale enterprise applications. In-depth experience inAI/ML and Data analytics services offered on Amazon Web Services and/or Microsoft Azure cloud solution and their interdependencies. Specializes in at least one of theAI/ML stack (Frameworks and tools like MxNET and Tensorflow, ML platform such as Amazon SageMaker for data scientists, API-drivenAIServices like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call). Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.

At Xerago, we believe in empowering individuals to script their own success stories as an AI Engineer. You will design, develop, and maintain sophisticated AI solutions, driving our application-engineering department forward with your proficiency in AI, ML, and Python. Your impact on organizational growth comes from successful deployment of AI solutions, accurate machine learning models, and efficient data processing. Collaborate with cross-functional teams to achieve project goals, while mentoring junior engineers when required. Technical Responsibilities: - Design, develop, and maintain sophisticated AI solutions within the application-engineering department using Python, AI, ML, LLM, and data mining. - Implement predictive modeling and machine learning algorithms to drive business impact, with a focus on efficiency and accuracy of data processing. - Leverage expertise in big data frameworks such as Hadoop and Spark for large-scale data analysis and processing tasks. - Collaborate with cross-functional teams to integrate AI solutions into existing systems, ensuring compatibility and seamless integration. Additional Technical Expectations: - Pursue relevant certifications such as TensorFlow Developer, AWS Certified Machine Learning Specialty, or equivalent credentials to stay updated on industry trends and best practices. - Demonstrate a commitment to producing high-quality work that exceeds client expectations, contributing to Xerago's reputation for innovation. Leadership Scope (not applicable for this role): - Managerial responsibilities are minimal in this role; however, the AI Engineer may be required to mentor junior engineers when necessary. - The ideal candidate should possess strong problem-solving skills, an ability to communicate complex technical concepts effectively, and a willingness to share knowledge within their team. Qualification: 1. Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field with a strong focus on AI and machine learning. 2. Strong expertise in Python, particularly in deep learning libraries such as TensorFlow and PyTorch (MUST Note: For fresher suggest Proficiency, for Experience show Strong Expertise). 3. Good to have knowledge in Natural Language Processing (NLP) and Robotics, specifically ROS (Robot Operating System). 4. AWS Certified Machine Learning Specialty (Good to have) 5. TensorFlow Developer (Good to have) 6. Strong communication, teamwork, adaptability, problem-solving, and mentoring abilities

Role Description: This is a full-time on-site role as a Machine Learning Engineer in Chennai. The Machine Learning Engineer will be responsible for pattern recognition, developing neural networks, applying statistical analysis, and implementing algorithms on a day-to-day basis. Responsibilities: Develop and deploy machine learning models: Design, build, train, and evaluate various models, including deep learning, natural language processing, and time series analysis models, leveraging your understanding of core ML concepts like supervised, unsupervised, and reinforcement learning paradigms. This includes experience with Transformer models and their applications. Data processing and feature engineering: Clean, transform, and prepare large datasets for model training and evaluation. Develop innovative feature engineering techniques to improve model performance. LLM and RAG development: Build and fine-tune LLMs for specific tasks related to voice and data analytics. Implement RAG systems to enhance LLM performance with external knowledge sources. Prompt-to-SQL generation: Develop models that can translate natural language queries into SQL queries, enabling users to easily access and analyze data. Data insights and visualization: Develop algorithms and tools to extract meaningful insights from data and present them clearly and concisely. Classifier development: Build and train classifiers for various tasks, such as sentiment analysis, topic classification, and intent recognition. This includes understanding different classification algorithms (e.g., logistic regression, support vector machines, decision trees) and performance metrics (e.g., precision, recall, F1- score). Model optimization and deployment: Optimize model performance for speed and accuracy. Deploy models to production environments using appropriate tools and technologies. Stay up-to-date: Keep abreast of the latest advancements in machine learning and related fields. Explore and experiment with new techniques and technologies. Collaborate effectively: Work closely with other engineers, product managers, and researchers to deliver high-quality solutions. Requirements: 2-4 years of experience developing and deploying machine learning models in a production environment. Strong understanding of fundamental machine learning concepts, including model selection, evaluation metrics, bias-variance tradeoffs, and regularization techniques. Solid grasp of neural networks, including different architectures (e.g., CNNs, RNNs, Transformers), activation functions, backpropagation, and optimization algorithms. Deep understanding of Transformer models, including attention mechanisms, selfattention, and different Transformer variants (e.g., BERT, GPT). Experience with classification modelling techniques, including handling imbalanced datasets, multi-class classification, and model interpretation. Strong programming skills in Python and experience with relevant libraries such as TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers. Specifically, experience fine-tuning and deploying Transformer models using these libraries. Nice to Have: Experience with cloud platforms such as AWS, Azure, or GCP, including deploying and managing Transformer models at scale. Experience with database technologies such as SQL and NoSQL. Experience with version control systems such as Git. Excellent communication and collaboration skills. Experience with LLMs, RAG, and prompt engineering, specifically using Transformerbased models, is a strong plus. Experience with voice data processing and analysis is a plus

Hello, Greetings from GlobalData!!! Job Opening for below roles @ GlobalData -Hyderabad. Data Science Senior Data Science Job Criteria :- Qualification: B.Tech/BE/MCA/M.Tech/B.Sc/M.Sc-(Computers) Experience Range : 2 to 5 years Key Skills : Python, SQL, Gen AI, LLM, Data Science Notice Period : Immediate joiners or with one month notice period Job Location : Hyderabad Work Mode : Hybrid Salary : best as per market standard's Detailed job description given below please go through to understand requirement. If requirement is matching to your profile share your updated resume @ mail id (m.salim@globaldata.com). Mention Subject Line :-Applying for Data Science @ GlobalData-Hyd. Please Share your details in the mail :- Your Full Name : Mobile # : Qualification : Company Name : Designation : Total Work Experience Years : Current CTC : Expected CTC : Notice Period : Present Location : If out-station willing to relocate to Hyd : Yes/No Job Description:- Data Scientist Location: Hyderabad, India Experience: 2+ years About the Role :- We are looking for a Data Scientist with at least 2 years of experience to join our Hyderabad team. The ideal candidate is skilled in Python and SQL, with a strong analytical mindset. Experience with Generative AI (GenAI) or Large Language Models (LLMs) is a plus. Responsibilities Analyze large datasets and extract actionable insights. Build and deploy machine learning models. Write efficient SQL queries for data extraction and analysis. Collaborate with cross-functional teams to deliver data-driven solutions. Present findings to technical and non-technical stakeholders. Requirements Bachelors or Masters in Computer Science, Statistics, Mathematics, Engineering, or related field. 2+ years of experience in Data Science or a similar role. Strong Python and SQL skills. Solid understanding of statistics, machine learning, and data visualization. Excellent problem-solving and communication skills. Preferred Experience with GenAI or LLMs. Familiarity with cloud platforms (AWS, GCP, Azure) and big data tools (Spark, Hadoop). Knowledge of deep learning frameworks (TensorFlow, PyTorch). Job Description: Senior Data Scientist Location: Hyderabad, India Experience: 5+ years About the Role :- We are seeking a Senior Data Scientist with at least 5 years of experience to join our Hyderabad team. The ideal candidate has strong expertise in Python and SQL, hands-on experience with Generative AI (GenAI) or Large Language Models (LLMs), and a proven ability to manage multiple projects. You will lead data science initiatives, ensure timely project delivery, and mentor junior team members. Responsibilities Lead and deliver multiple data science projects on schedule. Design, develop, and deploy advanced machine learning and GenAI/LLM solutions. Guide and mentor junior data scientists, providing technical direction and support. Collaborate with cross-functional teams to define project goals and deliverables. Communicate complex findings clearly to stakeholders at all levels. Requirements Bachelors or Masters in Computer Science, Statistics, Mathematics, Engineering, or related field. 5+ years of experience in Data Science or a similar role. Strong proficiency in Python and SQL. Hands-on experience with GenAI or LLMs. Proven project management and team leadership skills. Deep understanding of statistics, machine learning, and data visualization. Excellent problem-solving, communication, and organizational skills. Preferred Experience with handling data formats like structured (SQL), semi-structured (Elasticsearch) and unstructured (PDF, Images in S3) Experience with cloud platforms (AWS, GCP, Azure) and big data tools (Spark, Hadoop). Knowledge of deep learning frameworks (TensorFlow, PyTorch). Thanks & Regards, Salim (Human Resources)

Job Title: Generative AI Analyst Responsibilities: Large Language Model Data Evaluation & Narrations: Execute data evaluation, narration, and labeling tasks according to client requirements and guidelines with precision and attention to detail for AI model training Language Proficiency: Demonstrate a high level of English language proficiency (C1 level or above) in both written and verbal communication. C1 TOEFL or ielts CERTIFICATION OR Equivalent Adherence to Guidelines : Follow client-specific instructions and guidelines meticulously to produce consistently accurate annotations. Quality Assurance: Perform quality checks on annotated data to maintain high standards of accuracy and completeness. Communication: Collaborate effectively with team members and project managers to address queries and ensure smooth workflow. Feedback Integration: Actively participate in feedback sessions and incorporate constructive feedback into your work to improve annotation quality. Requirements: Language Skills: Proficiency in English at a C1 level or higher, both written and verbal. Attention to Detail: Strong attention to detail and ability to follow guidelines accurately. Adaptability: Ability to adapt to changing project requirements and priorities. Team Collaboration: Strong team collaboration and communication skills. Tech Savvy: Comfortable working with annotation tools and technology platforms.. Generative AI Understanding: Familiarity with generative AI concepts and a keen interest in contributing to the advancement of language generation technologies. Autonomous vehicle: (Good to have skills) Understanding of perception and prediction labeling work in AV domain is a plus.

Job Title: AI Developer Supply Chain Management Location: Permanent Remote Job Type: Full-time Team: Product AI Engineering We are looking for a talented LLM Developer to join our AI Engineering team and contribute to the development of the SCM Expert AI Agent the core brain behind AI capabilities like demand forecasting, anomaly detection, ETA prediction, and route optimization in the FarmToPlate (F2P) platform. In this role, you will focus on integrating and optimizing LLM-based agentic architectures using frameworks like LangChain, CrewAI, and RAG pipelines. Youll work closely with traditional ML developers and backend engineers to deploy intelligent, explainable, and real-time decision agents for supply chain management. Responsibilities: Design, build, and optimize LLM-based agents using LangChain, CrewAI, or custom wrappers. Implement RAG pipelines with vector stores (e.g., FAISS, ChromaDB) and embedding models. Develop LLM-powered tools for demand forecasting, query understanding, anomaly explanations, and summarization. Integrate agents with internal and external data sources using tools like MongoDB, Sklearn datasets, or Browsing Agents. Implement prompt engineering, agent memory, and context-chaining for more dynamic agent behavior. Collaborate with data science and product teams to translate SCM logic into agentic workflows. Expose models and agents through APIs using FastAPI, including role-based access if needed. Optimize runtime performance with quantization, PEFT (parameter-efficient finetuning), and model caching. Track experiments, versions, and deployment artifacts using tools like MLflow, SageMaker, or custom registries. Requirements: 3-5 years of experience working on Python-based AI systems. Strong understanding of LLMs, Transformers, Prompt Engineering, and conversational AI. Hands-on experience with LangChain, CrewAI, OpenAI/GPT APIs, or Hugging Face Transformers. Familiarity with RAG concepts, vector databases (FAISS, Chroma), and embedding techniques. Good knowledge of API frameworks (FastAPI/Flask) and working with JSON schema-driven inputs. Basic understanding of traditional ML models and workflows (e.g., regression, classification, anomaly detection). Comfortable integrating external data tools and APIs into LLM pipelines. Bonus Points For Experience building Agentic RAG systems that combine logic, tools, memory, and models. Knowledge of Open Source LLM tuning using PEFT, LoRA, bitsandbytes, Unsloth, etc. Familiarity with SageMaker, EKS, or deploying custom models to the cloud. Experience in supply chain/logistics, or working with ERP/SCM structured data. Built monitoring dashboards using Evidently.ai or similar model observability tools. Why Join Us Be part of a domain-driven AI platform blending supply chain expertise with modern agentic LLM architectures. Work on real-world use cases that impact farm-to-plate food systems at scale. Collaborate with a fast-moving, cross-functional team that values innovation, ownership, and outcome. Learn and grow in a modular, full-stack AI environment where your ideas become deployed APIs. Enjoy flexibility in remote, experimentation, and continuous learning.

Key points: Should have 2+ years of professional backend building experience Should have experience of working in Java/C++/Go with experience in Multithreading, object-oriented design patterns, microservices architecture Experience developing cloud architecture on leading cloud providers (Azure AWS/ GCP) is a must Prior work with LLM/ML applications would be a bonus.

Job Description Management Level: Ind & Func AI Decision Science Analyst/Consultant Location: Bengaluru (Bangalore), Gurugram (Gurgaon), Hyderabad, Chennai. Must-have skills: Programming languages -Python/R, Generative AI, Large Language Models (LLMs), ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API, RAG Applications. Good to have skills : Big data technologies such as Spark or Hadoop,AI model explainability(XAI),bias detection and AI ethics. Familiarity with Edge AI and deploying models on embedded devices for industrial automation. Experience with Reinforcement Learning (RL) and AI-driven optimization techniques. Job Summary We are looking for a Data Scientist / AI Specialist with 2-9years of experience to join our team and work on client projects in the Automotive & Industrial sectors. This role will involve leveraging traditional Machine Learning (ML), Generative AI (GenAI), Agentic AI, and Autonomous AI Systems to drive innovation, optimize processes, and enhance decision-making in complex industrial environments. Prior experience in the Auto/Industrial industry is a plus, but we welcome candidates from any domain with a strong analytical mindset and a passion for applying AI to real-world business challenges. Roles & Responsibilities: Develop, deploy and monitor AI/ML models in production environments & enterprise systems, including predictive analytics, anomaly detection, and process optimization for clients. Work with Generative AI models (e.g., GPT, Stable Diffusion, DALLE) for applications such as content generation, automated documentation, code synthesis, and intelligent assistants. Implement Agentic AI systems, including AI-powered automation, self-learning agents, and decision-support systems for industrial applications. Design and build Autonomous AI solutions for tasks like predictive maintenance, supply chain optimization, and robotic process automation (RPA). Work with structured and unstructured data from various sources, including IoT sensors, manufacturing logs, and customer interactions. Optimize and fine-tune LLMs (Large Language Models) for specific business applications, ensuring ethical and explainable AI use. Utilize MOps and AI orchestration tools to streamline model deployment, monitoring, and retraining cycles. Collaborate with cross-functional teams, including engineers, business analysts, and domain experts, to align AI solutions with business objectives. Stay updated with cutting-edge AI research in Generative AI, Autonomous AI, and Multi-Agent Systems. Professional & Technical Skills: 3-5 years of experience in Data Science, Machine Learning, or AI-related roles. Proficiency in Python (preferred) or R, and experience with ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API. Strong understanding of Generative AI, Large Language Models (LLMs), and their practical applications. Hands-on experience in fine-tuning and deploying foundation models (e.g., OpenAI, Llama, Claude, Gemini, etc.). Experience with Vector Databases (e.g., FAISS, Chroma, Weaviate, Pinecone) for retrieval-augmented generation (RAG) applications. Knowledge of Autonomous AI Agents (e.g., AutoGPT, BabyAGI) and multi-agent orchestration frameworks. Experience working with SQL and NoSQL databases. Familiarity with cloud platforms (AWS, Azure, or GCP) for AI/ML model deployment. Strong problem-solving and analytical thinking abilities. Ability to communicate complex AI concepts to technical and non-technical stakeholders. Bonus: Experience in Automotive, Industrial, or Manufacturing AI applications (e.g., predictive maintenance, quality inspection, digital twins). Additional Information: Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record /MBA from top-tier universities. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Job Qualifications Job Qualifications Experience: Minimum 2-9 years of relevant Data Science, Machine Learning or AI-related roles., Exposure to Industrial & Automotive Firms or Professional Services. Educational Qualification: Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record or MBA from top-tier universities.

• Collaborate with cross-functional teams and stakeholders to understand business requirements and align AI solutions with objectives. • Design, develop, and deploy machine learning models and algorithms, including LLM-based solutions and fine-tuning. • Conduct data analysis and preprocessing to ensure high-quality input for AI models. • Evaluate and optimize AI system performance, including monitoring for model drift. • Stay updated on emerging AI technologies and assess their potential business applications. • Provide technical leadership and mentorship to team members on AI/ML best practices. • Communicate findings and insights to stakeholders effectively. • Participate in project planning, estimation, and execution. • Develop and optimize RAG architecture using Vector DB or Knowledge Graph. • Engineer robust ML pipelines and infrastructure using on-premises/cloud tools.

Collaborate with cross-functional teams and stakeholders to understand business requirements and align AI solutions with objectives. • Design, develop, and deploy machine learning models and algorithms, including LLM- based solutions and fine-tuning. • Conduct data analysis and preprocessing to ensure high-quality input for AI models. • Evaluate and optimize AI system performance, including monitoring for model drift. • Stay updated on emerging AI technologies and assess their potential business applications. • Communicate findings and insights to stakeholders effectively. • Develop and optimize RAG architecture using Vector DB or Knowledge Graph. • Engineer robust ML pipelines and infrastructure using on-premises/cloud tools. • Establish CI/CD practices and automated testing frameworks for AI systems.

Tech stack required: Programming languages: Python Public Cloud: AzureFrameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool. Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production Nice to have requirements to the candidate Excellent communication skills, both written and verbal. Strong problem-solving and critical-thinking abilities. Effective leadership and mentoring skills. Ability to collaborate with cross-functional teams and stakeholders. Strong attention to detail and a commitment to delivering high-quality solutions. Adaptability and willingness to learn new technologies. Time management and organizational skills to handle multiple projects and priorities.

OUR CLIENT is ranked #1 on Glassdoor's 2023 Best Place to Work List. Here's why. At OUR CLIENT's mission is to be living proof you can win in business while being human-first. OUR CLIENT's industry-leading platform helps companies of all sizes and industries build durable businesses. OUR CLIENT offers a powerful set of customer success, product, community and education solutions that enable businesses to scale efficiently, create alignment, and have a holistic view of their customers all of which help increase product adoption, prevent churn, and grow renewals and expansions. Hundreds of companies use our software, including nearly 200 publicly traded organizations and industry leaders such as GE Digital, SAP Concur, and Zendesk. We have offices in the US, UK, Netherlands, Israel, Japan, and India. OUR CLIENT joined the Vista Equity Partners portfolio in 2020. In 2021, we won their Excellence in Engineering award for our product and engineering advancements. OUR CLIENT has also been named one of the top 100 private cloud companies by Forbes, one of the fastest-growing private companies in America by Inc. Magazine, and one of 20 Great Workplaces in Tech by Fortune Magazine. With diversity and inclusion at the forefront of our values, OUR CLIENT promotes a culture that celebrates diversity and inclusiveness regardless of but not limited to, race, gender, sexual orientation, family status, religion, ethnicity, national origin, physical disability, veteran status, or age. Job Summary: OUR CLIENT is building something new: Managed AI Services, a category-defining initiative focused on delivering high-value, AI-augmented outcomes. Unlike traditional services, this function is designed and operated as a scalable capability that integrates human expertise and oversight with large language models (LLMs) and AI Agents to deliver repeatable, premium experiences across the post-sales customer journey. This function represents a new category of value creation at OUR CLIENT distinct from traditional servicesenabling us to offer outcomes with the scale, efficiency And repeatability of SaaS offering while retaining the customizability and white glove quality Office Service Offering quality that our customers expect. The group will serve as a central operational layer for AI-augmented work, partnering closely with product, engineering, customer success, education, and analytics teams. As an Applied AI Engineer (Models, Prompts, Reasoning), you will operate at the intersection of model capabilities, reasoning frameworks, agentic behavior, and AI feature delivery. You won’t just refine large language models—you’ll design and build end-to-end LLM-based agentic applications, from model selection and evaluation to multi-step reasoning and prompt chaining, all the way to integrating intelligent decision-making flows into production systems. This role requires a strong technical foundation in AI/ML, deep learning, and NLP, along with hands-on experience in prompt engineering, retrieval-augmented generation (RAG), and function calling to optimize AI performance. What you will do: Evaluate and integrate LLMs from OpenAI, Anthropic, Meta (Llama 2), and other vendors. Develop multi-step reasoning and prompt-chaining frameworks for complex AI applications. Optimize AI models by tuning temperature, top_p, and frequency penalties for high-quality outputs. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, or Weaviate. Design and orchestrate multi-model ecosystems that ensure factual accuracy and contextual adaptability. Utilize self-critique and reflection prompts to improve model responses and reduce hallucinations. Collaborate cross-functionally with Product, Engineering, and Research teams to deploy AI-driven solutions at scale. Continuously test and refine LLM behaviors using A/B testing, model evaluation frameworks, and feedback loops. Who you are: 5–8+ years of experience in AI, Machine Learning, and Natural Language Processing (NLP). 2–3+ years of hands-on experience working with LLMs and AI-powered applications. Strong knowledge of LLM architectures, including GPT-4, Claude, Llama 2, Mistral, and fine-tuning methodologies. Expertise in prompt engineering, function calling, and agentic workflows. Experience with retrieval-augmented generation (RAG) and integrating vector databases into AI pipelines. Proficiency in Python, LangChain, Hugging Face, OpenAI SDKs, and AI orchestration tools. Familiarity with multi-model orchestration, decision logic, and self-correcting AI behaviors. Strong understanding of LLM safety, bias mitigation, and ethical AI development. Experience with deploying AI systems in production, API integration, and cloud-based AI solutions. Bonus Skills (Nice to Have): Hands-on experience fine-tuning open-source LLMs. Knowledge of advanced reasoning frameworks (Chain-of-Thought, Tree of Thoughts). Experience working with LLM evaluation metrics (BLEU, perplexity, win-rate comparisons). Job Benefits At OUR CLIENT, the mission is to be living proof you can win in business while being human first. Your job should never be a barrier to your happiness—it should be an avenue to achieve it. At OUR CLIENT, we’re passionate about achieving our goals—at the office and everywhere—and we work every day to create an environment that nurtures our best selves. Here are OUR CLIENT’s 5 core values Golden Rule : We try to practice the Golden Rule by exercising reliability, trust and giving back to each other and our community. Success for All : We believe in success for our stakeholders—whether our teammates, clients or shareholders—comes with a sincere focus on continuous learning, selfless teaching and making a difference in each other’s lives. Child-like Joy : We aspire to experience child-like joy in our work and lives, injecting a spirit of passion, optimism and laughter into everything that we do. Shoshin : We believe in a beginner’s mind. Don’t surround yourself with people like you--diversity breeds creativity. Stay Thirsty, My Friends : We believe in a totally internally-driven strive for greatness. The solution is to think more, not do more. Why You’ll Love It Here Our Attitude: We’ve created a new category from scratch and we continue to be the thought leader in Customer Success. Our Leadership: We offer the leading tech solution for driving Customer Success. Our ROI: Reduce customer churn, increase up-sell, and improve customer satisfaction. Our Technology: Our technology allows companies to drive retention and growth by delivering the value customers demand. Our Impact: In addition to helping companies grow, we’ve committed to $100 million in wage expansion for underrepresented groups over the next few years. Our Clients: Big companies like Box, Adobe, Marketo, and many others. Our Team: Our team is composed of innovative Customer Success thought leaders and experts in their field from various industries.

Role: Gen AI Engineer Exp: 5 to 8 yrs. Loc: Bangalore, Pune, Hyderabad NP: Immediate joiners, who can join in 30 days. Required Skills: Python, Large Language Models (LLM), Machine Learning (ML), Generative AI

Develop applications for investment management and trading/Valuation support using Python, React, SQL , FastAPI , and AWS and LLM Unit Testing Daily Scrums with client Required Candidate profile 5+ years of Python with Flask, FastAPI, etc. Experience with RestAPI development Hands on UI Development in React, Experience with cloud Azure/ AWS Experience with LLM /Langchain and DEvops

Customize Llama or leverage OpenAI to develop custom frameworks for investment management alternate data analysis Use Orchestration tools like N8n for document ingestion Setup on cloud or private using Coreweave Lead Machine Learning and UI Engineers Required Candidate profile 5+ years of development experience in .NET , Python and Azure 3+ years of experience in Data Science along with hands on GenAI and LLMs Experience with VectorDB, documentation ingestion workflows etc.

Key points: Should have 2 years+ frontend development experience in building web applications Should be proficient in React, Next.js, Rest APIs, Tailwind css, Typescript Prior experience of dealing with serverless API (Lambda, Edge) is a bonus Experience of analysing performance through frontend monitoring platform Prior work with LLM/ML applications is a bonus. Mandatory Key Skills frontend development,Typescript*,Rest APIs*,Next.js*,Tailwind CSS*,LLM,Lambda,Machine Learning,React*,Serverless API

Mandatory Skills Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have skills - Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

Lead AI Architect: We are seeking a highly skilled AI Architect to lead our team in developing cutting-edge generative AI solutions. This role requires a deep understanding of AI/ML concepts, strong technical expertise, and exceptional leadership abilities. As the Lead AI Architect, you will be the technical authority responsible for defining the strategy, architecture, and execution of cutting-edge generative AI initiatives. You will lead a talented team, driving the development of innovative solutions from concept through production deployment. This role demands a deep understanding of state-of-the-art AI models, advanced techniques like Retrieval-Augmented Generation (RAG) and fine-tuning, robust MLOps practices, and scalable cloud deployment strategies Role & responsibilities 1. Technical Vision & Architecture: a. Define and champion the technical vision and architectural roadmap for generative AI solutions (LLMs, Diffusion Models, Multimodal Models, etc.). b. Design, architect, and guide the development of sophisticated generative AI systems, incorporating techniques like fine-tuning, prompt engineering, and Reinforcement Learning from Human Feedback (RLHF). c. Architect and implement advanced Retrieval-Augmented Generation (RAG) pipelines, including vector database selection/optimization, chunking strategies, and multimodal RAG approaches. d. Ensure solutions are scalable, performant, cost-effective, reliable, and adhere to responsible AI principles (fairness, transparency, security). e. Stay relentlessly current with academic research and industry advancements in generative AI, MLOps, and related technologies, integrating relevant innovations. 2. MLOps & Lifecycle Management: a. Lead the design and implementation of robust MLOps pipelines for the entire generative AI lifecycle: data ingestion/preprocessing, model training/fine-tuning, validation, versioning (data, code, models), automated deployment, and continuous monitoring. Job Opening b. Establish best practices for model evaluation, performance tracking, drift detection, and ongoing optimization of generative models in production. c. Champion automation, reproducibility, and governance across all AI/ML workflows. 3. Deployment & Integration: a. Oversee the deployment of fine-tuned models and complex AI systems into scalable production environments using cloud platforms (AWS, GCP, Azure, potentially NVIDIA AI Enterprise). b. Design and implement containerized deployments (Docker, Kubernetes) and serverless architectures for AI model serving. c. Develop robust APIs (RESTful, gRPC) for seamless integration of AI capabilities into broader applications and services. d. Optimize models for inference speed and cost efficiency. 4. Leadership & Collaboration: a. Lead, mentor, and inspire a team of AI/ML engineers and data scientists. b. Collaborate closely with product managers, software engineers, data engineers, and business stakeholders to translate requirements into actionable AI strategies and technical designs. c. Effectively communicate complex technical concepts, architectural decisions, and project status to both technical and non-technical audiences, including executive leadership. d. Foster a culture of innovation, experimentation, and continuous improvement within the AI team Preferred candidate profile : • Typically 8-10+ years of hands-on experience in designing, building, and deploying production-grade AI/ML systems, with a significant recent focus (3+ years) on Generative AI. • Generative AI Expertise: Deep understanding and practical experience with foundational models (e.g., GPT series, Llama series, Stable Diffusion, multimodal models), transformer architectures, and key techniques like fine-tuning, prompt engineering, and RAG. • RAG Proficiency: Proven experience architecting and implementing RAG systems, including familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, ChromaDB) and embedding techniques. • MLOps Mastery: Demonstrable experience designing, building, and managing end-to-end MLOps pipelines using relevant tools and platforms (e.g., MLflow, Kubeflow, Vertex AI Pipelines, SageMaker Pipelines, Azure ML). • Programming & Frameworks: Expert-level proficiency in Python and core AI/ML libraries/frameworks (e.g., PyTorch, TensorFlow/Keras, JAX, Hugging Face ecosystem, LangChain, LlamaIndex). • Cloud Platforms: Strong hands-on experience with at least one major cloud provider (AWS, GCP, Azure) and their associated AI/ML services (e.g., SageMaker, Vertex AI, Azure Machine Learning). • Deployment Skills: Experience with containerization (Docker, Kubernetes), API development (REST, gRPC), and model serving/optimization techniques. • Leadership: Proven track record of technical leadership, mentoring teams, and successfully delivering complex AI projects from ideation to production. • Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical ideas clearly and concisely. • Methodologies: Familiarity with Agile development practices and version control systems (Git). • Education: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field. (PhD preferred but not required). Preferred Qualifications : • Education: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field. (PhD preferred but not required). • Experience with multimodal generative models and RAG. • Experience with distributed training and large-scale model optimization (e.g., quantization, pruning). • Familiarity with data engineering tools and platforms (e.g., Spark, Kafka, Airflow). • Contributions to relevant open-source projects or publications in top AI/ML venues.

Experience - 8 - 10 years Location - Bengaluru Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Build and manage LLMOps pipelines for fine-tuning, evaluating, and deploying large language models (e.g., OpenAI, HuggingFace Transformers, custom LLMs). Use Kubeflow and Kubernetes to orchestrate reproducible, scalable ML/LLM workflows. Implement CI/CD pipelines for ML projects using GitHub Actions , Argo Workflows , or Jenkins . Automate infrastructure provisioning using Terraform , Helm , or similar IaC tools. Integrate model registry and artifact management with tools like MLflow , Weights & Biases , or DVC . Manage containerization with Docker and container orchestration via Kubernetes . Set up monitoring , logging , and alerting for production models using tools like Prometheus , Grafana , and ELK Stack . Collaborate closely with Data Scientists and DevOps engineers to ensure seamless integration of models into production systems. Ensure model governance, reproducibility, auditability, and compliance with enterprise and legal standards. Conduct performance profiling, load testing, and cost optimization for LLM inference endpoints. Required Skills and Experience Core MLOps/LLMOps Expertise 5+ years of hands-on experience in MLOps/DevOps for AI/ML. 2+ years working with LLMs in production (e.g., fine-tuning, inference optimization, safety evaluations). Strong experience with Kubeflow Pipelines , KServe , and MLflow . Deep knowledge of CI/CD pipelines with GitHub Actions , GitLab CI , or CircleCI . Expert in Kubernetes , Helm , and Terraform for container orchestration and infrastructure as code. Programming & Frameworks Proficient in Python , with experience in ML libraries such as scikit-learn , TensorFlow , PyTorch , Hugging Face Transformers . Familiarity with FastAPI , Flask , or gRPC for building ML model APIs. Cloud & DevOps Hands-on with AWS , Azure , or GCP (preferred: EKS, S3, SageMaker, Vertex AI, Azure ML). Knowledge of model serving using Triton Inference Server , TorchServe , or ONNX Runtime . Monitoring & Logging Tools: Prometheus , Grafana , ELK , OpenTelemetry , Sentry . Model drift detection and A/B testing in production environments. Soft Skills Strong problem-solving and debugging skills. Ability to mentor junior engineers and collaborate with cross-functional teams. Clear communication, documentation, and Agile/Scrum proficiency. Preferred Qualifications Experience with LLMOps platforms like Weights & Biases , TruEra , PromptLayer , LangSmith . Experience with multi-tenant LLM serving or agentic systems (LangChain, Semantic Kernel). Prior exposure to Responsible AI practices (bias detection, explainability, fairness).

About the Role : A global leader in technology innovation is seeking a highly skilled C++ Developer with a passion for competitive programming and logical reasoning to join our team. This critical role will focus on creating high-quality reasoning datasets to train and improve Large Language Models (LLMs). You will design structured programming challenges and reasoning tasks to enhance the problem-solving capabilities of advanced AI systems. This is an exceptional opportunity for individuals with strong problem-solving expertise to contribute to cutting-edge AI development and directly impact the future of LLMs. Job Responsibilities : - Dataset Creation : Design and create structured reasoning tasks rooted in programming challenges, specifically in C++, to effectively train LLMs. This includes defining problem statements, specifying input/output formats, and generating diverse test cases. - Problem Decomposition : Develop datasets that test and improve an LLM's ability to solve complex, multi-step problems, requiring clear and logical explanations of the solution process. This will involve breaking down problems into smaller, manageable sub-problems. - Collaboration : Collaborate closely with research scientists and engineers to ensure task objectives align with model training goals and contribute to the overall improvement of the LLM's performance. - Iteration and Refinement : Incorporate feedback from model performance analysis to iterate on and refine task designs, ensuring they effectively target areas for improvement in the LLM's reasoning and problem-solving abilities. - Quality Assurance : Maintain consistency and clarity in task descriptions, ensuring they meet high-quality standards for accuracy, completeness, and readability. This includes rigorous testing and validation of the generated datasets. - Documentation : Create and maintain clear documentation for the designed tasks, including problem descriptions, solution explanations, and any relevant metadata. Job Requirements : - Experience : At least 3 years of experience in software development, with a strong focus on C/C++ programming. - Programming Proficiency : Demonstrable expertise in C/C++ with a strong understanding of data structures and algorithms. - Analytical Skills : Excellent analytical and problem-solving skills, with the ability to break down complex problems into structured, logical steps. - Communication Skills : Proficient in English, with excellent written communication skills for crafting clear, concise, and logical explanations of programming solutions and reasoning processes. - Attention to Detail : Meticulous attention to detail in designing programming and reasoning tasks, ensuring accuracy and consistency. - Problem-Solving Prowess : A passion for problem-solving and a strong aptitude for logical reasoning. - Competitive Programming (Preferred) : A profile on platforms like LeetCode, HackerRank, Codeforces, or GitHub that demonstrates advanced problem-solving skills and competitive programming experience is a significant plus. - AI/ML Interest (Preferred) : Familiarity with or a strong interest in the field of Artificial Intelligence and Machine Learning, particularly related to LLMs, is a plus. Mandatory Skills : - C++ : 3+ years of experience Bonus Skills (Considered a Plus) : - Experience with other programming languages (e.g., Python). - Experience with data manipulation and analysis tools. - Knowledge of software testing methodologies. - Contributions to open-source projects Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

Role and responsibilities: Implement and supervise execution of review plans that meet both our standards and project specific requirements. Recommend and drive best practices in review as a trusted advisor to both internal and external stakeholders. Communicate directly with counsel, client, and review team on substance and progress of review. Assist in development of matter-specific review project plans that address review workflow strategy and optimal application of technology. Establish review quality control measures and manage document review teams to ensure adherence to our playbook, execution of throughput goals & quality deliverables. Collaborate with our teams, including AI experts and data project managers. Consult on technology efficiency drivers for redaction application and privilege logging. Provide client- and case-specific subject matter expertise. Provide feedback, training, and direction to Review Associates and Senior Associates while building cohesion within the team. Participate in process improvement initiatives and other related duties as assigned. Required skills and experience: 5+ years of experience as a document review manager with a review provider or law firm Bachelors or Masters degree in law Experience managing document review projects for complex financial services and pharmaceutical clients preferred. Experience managing non-litigation projects like data breach of contract extraction review projects a plus. Ability to lead and motivate diverse attorney teams in completion of review workflows while adhering to established accuracy targets, project timelines, and budget parameters. Self-motivated, with strong sense of ownership and commitment to client satisfaction Knowledge of litigation discovery process and objectives Strong written and oral communication skills suited to a client-facing role, careful attention to detail, and general technical aptitude. Ability to manage competing priorities and work independently or as part of a team. Proficiency as an end user in Relativity, Brainspace, Blackout or comparable platforms Experience establishing matter-tailored quality control measures and managing reviews across a variety of discovery matters.

Skills: Excellent knowledge of Data Structures and Algorithms Great programming skills in Python Working knowledge C++ Experience in AI/ML, Data Science, CNN, RNN, LLM Classification, Clustering. Job Responsibilities: Designing and developing AI/ML algorithms to solve different technical problems in the domain of 3GPP. Explaining the designed data science algorithms clearly in document and presenting the same to support the innovation. Working in a team and share the responsibilities of integration, productisation and deployment.

We're hiring a Head of Engineering at Zonka Feedback . Own the Stack, Scale AI, Lead the Vision!! Company Profile: Zonka Feedback is a powerful, AI-driven customer experience (CX) and feedback platform that helps businesses capture feedback, measure, and improve customer satisfaction across various touchpoints, and drive strategic growth. With seamless integrations into major CRMs like Salesforce and HubSpot, Zonka Feedback empowers brands worldwide to listen to customer voices and make data-driven decisions through multi-channel feedback collection, advanced reporting, and AI insights. Get to know more about us at www.zonkafeedback.com We're building an AI-first SaaS platform that's redefining how feedback systems work and combines: Smart prompting and automation Seamless ML model integration and fine-tuning Rich analytics and actionable insights Scalable infra to handle millions of requests and third-party integrations Agentic, autonomous workflows Job Role: We are looking for a dynamic Head of Engineering to architect and build scalable, AI-powered systems using modern technologies including Node.js, Python, React, AWS, and Serverless frameworks. In this role, you will play a critical part in shaping our core product by integrating advanced AI/ML models and developing intelligent automation workflows. As a key technical leader, you will guide a lean team of engineers, drive high-impact architectural decisions, and ensure the reliability, security, and performance of our systems. Ideal candidates have 7 to 15+ years of software development experience, with deep expertise in full-stack development, cloud architecture, and AI/ML integration. They have a proven track record of leading teams in fast-paced SaaS or startup environments, along with hands-on experience working with large-scale datasets, vector databases, and advanced NLP and LLM technologies . Key Responsibilities: Drive the engineering vision and execution for Zonkas AI-first customer experience platform Build and integrate ML/NLP systems, including LLMs and vector databases Architect and develop scalable systems using Node.js, Python, React, AWS, and Serverless Design and implement AI-powered workflows and automation pipelines Optimize infrastructure, DevOps, CI/CD , monitoring, and cost efficiency Lead and mentor a lean team of engineers; drive hiring and performance Collaborate with product and design teams to execute the product roadmap Maintain high code quality, system reliability, and security Leverage modern tools like GitHub Copilot, WindSurfer, and Cursor to drive productivity Requirements: 7 - 15 years of hands-on software development including full-stack development and system architecture Strong background in NLP, ML, and deploying LLM-based solutions in production environments Skilled in prompt engineering and RAG architecture Experience working with large datasets, ElasticSearch, and vector databases Strong expertise in Node.js, Python, AWS, React and scalable systems architecture Prior experience building and leading engineering teams in SaaS or startup environments Ability to balance leadership, architecture, and hands-on coding Familiarity with DevOps, CI/CD, infrastructure monitoring, and security best practices Excellent problem-solving, communication, and team-building skills If this sounds like you, we are here to have the next talk. Share your resume on hr@zonkafeedback.com