556 Generative Ai Jobs - Page 11

We are seeking a talented Java backend Software Engineer with expertise in software engineering to join our team. As a Full Stack Software Engineer, your primary responsibility will be to develop & integrate Generative AI solutions that focus on technology improvements. Specifically, you will be working on projects involving Generative AI solutions for Technology Assistants & Data Management Efficiencies and will contribute for Java backend development such as IDE plugins Data Connections & Integrators. Responsibilities : - Collaborate with cross-functional teams such as Data Scientists, Product Partners and Partner Team Developers to identify opportunities for process improvements that can be solved using machine learning and generative AI. - Write clean, high-performance, high-quality, maintainable code. - Create connectors to various Content and Collaboration tools using tool specific API's such as Jira, Slack, Git etc - Create backend applications using Java, docker & in-house frameworks to orchestrate AI applications - Design and develop Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions. - Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs. - Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications. Requirements: - A Master's or Ph.D. degree in Computer Science or a related field. - Proven experience working as a Software Engineer, with a focus on Java, and exposure to Generative AI Applications such as chatGPT. - Strong proficiency in programming languages such as Java, Kotlin, Scala etc ( Mandatory) - Experience or Exposure in creating IDE Plugins for PyCharm, VS Code, IntelliJ & Web Consoles ( Nice to have ) - Experience in python and data pipelines ( nice to have) - Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies. - Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Nice to have ) - Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders. - Proven ability to adapt and learn new technologies and frameworks quickly. - A proactive mindset with a passion for continuous learning and research. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Develop and maintain responsive web applications using ReactJS Manage application state using React Hooks or Redux Toolkit Integrate and consume RESTful APIs for frontend-backend communication Implement quality assurance best practices including validations and error handling Collaborate using Git and manage workflows through CI/CD pipelines Work with the team on repository setup and code management Collaborate with backend developers to integrate database systems Contribute to Gen AI feature integrations and enhancements Ensure performance optimization and code scalability Primary Skills: Proficient in Full Stack Development/UI development with ReactJS Strong experience with API integrations State management using React Hooks or Redux Toolkit Familiarity with QA processes, validations, and automated deployment using CI/CD tools Solid understanding of Git workflows and version control Secondary Skills: Working knowledge of Generative AI concepts and applications Experience with repository creation and codebase setup Exposure to backend database integration (e.g. PostgreSQL, OpenSearch etc.) Familiarity with Node.js or backend frameworks is a bonus

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking a highly skilled Generative AI Senior Lead with 11+ Years of IT industry experience in which 5/6 years should be in AI/ML/DS domain, including Gen AI technologies to lead the design and deployment of cutting-edge AI solutions. The ideal candidate will possess deep expertise in Generative AI , strong analytical skills, and excellent communication abilities to engage with clients and internal teams. This role involves designing AI architectures, implementing scalable models, and ensuring solutions align with business objectives. Roles & Responsibilities: Client Interaction: Collaborate with clients to understand business needs and define AI solutions. Solution Design: Develop AI architectures addressing client objectives and technical requirements. Metrics Definition: Define success criteria and measurable KPIs with stakeholders. Technical Implementation: Guide teams in deploying AI solutions efficiently. Performance Monitoring: Ensure AI model accuracy and recommend improvements as needed. Client Collaboration: Act as the main point of contact between clients and internal teams. Knowledge Sharing: Keep up with Generative AI advancements and contribute insights. Documentation: Maintain detailed technical reports and project records. Solution Design & Communication: Ability to design end-to-end AI solutions, from requirement elicitation to deployment strategy. Experience in architecting systems including data preprocessing, model integration, and optimization. Excellent verbal and written communication skills for client engagement and stakeholder Your Profile Technical Proficiency: Machine Learning Algorithms: Linear/logistic regression, decision trees, random forests, SVMs, neural networks. Data Science Tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras. Cloud Platforms: AWS, Azure, GCP. Natural Language Processing (NLP): Transformer models, attention mechanisms, word embeddings. Computer Vision: CNNs, RNNs, object detection. Robotics: Reinforcement learning, motion planning, control systems. Data Ethics & Responsible AI: Strong understanding of bias in ML, algorithmic fairness, ethical data handling, and transparency. Solution Design & Communication: Ability to design end-to-end AI solutions, from requirement elicitation to deployment strategy. Experience in architecting systems including data preprocessing, model integration, and optimization. Excellent verbal and written communication skills for client engagement and stakeholder presentations. Secondary Skill Set: Domain Knowledge: Understanding of industry applications (healthcare, finance, manufacturing). Project Management: Ability to oversee timelines, milestones, and deliverables, coordinating cross-functional teams. Data Understanding: Strong grasp of feature engineering, preprocessing, and quality assurance.

Join us for an exciting SDE Traineeship at Meesho. Based on the performance at Meesho, successful candidates will be considered for a full-time opportunity (FTE). The FTE salary offered will be INR 20,00,000 p.a. fixed + Benefits . Position: Software Development Engineer - Trainee Location : Bengaluru APPLY HERE: https://p.hck.re/6TcJ About the role: As an SDE Trainee , we expect you to be motivated in solving real-life complex problems and creating compelling experiences for our resellers. Being a small company we have a culture of creative problem- solving, intellectual design, fast-paced development, and passionate product delivery. The pace of our growth is incredible. If you want to tackle hard, interesting and UNIQUE problems, and create an impact within an entrepreneurial environment, JOIN US! Key Responsibilities: Collaborate with teams to develop new features for Meesho customers and suppliers Leverage state-of-the-art technologies and write highly performant code Take end-to-end ownership of features, from ideation to production Technical Requirements: 0-1 years of experience Strong problem-solving skills Excellent understanding of data structures and algorithms, and their space & time complexities Strong hands-on and practical working experience with at least one programming language: Java/Python/Javascript Excellent coding skills should be able to convert design into code fluently.

Design & develop end-to-end machine learning models & GenAI workflows Fetch & process data from BigQuery & various sources for model development Build & deploy models using Python & frameworks like Scikit Learn, XGBoost/CatBoost, TensorFlow & Gemini Required Candidate profile 4+ years of experience in the Data Science domain and should have hands on exp in Python, Machine Learning and/or Generative AI (Artificial Intelligence) This is an Individual contributor role

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking an 6 Years of IT industry experience in which 2/3 years should be in AI/ML/DS domain, including Gen AI technologies. We are seeking an accomplished Generative AI Technical Lead to spearhead the development, implementation, and optimization of Generative AI solutions. As the Lead Developer, you will play a pivotal role in prompt engineering, pipeline creation, workflow establishment, and ensuring the quality of the technical outputs generated by the team. This role requires strong technical expertise in Generative AI, hands-on experience in development, and the ability to lead and guide a team effectively. Primary Skill Set: Generative AI Expertise: Good understanding of various Generative AI techniques, including GANs, VAEs, and other relevant architectures. Proven experience in applying these techniques to real-world problems for tasks such as image and text generation. Conversant with Gen AI development tools like Prompt engineering, Langchain, Semantic Kernels, Function calling. Exposure to both API based and opens source LLMs based solution design. Technical Proficiency: Machine learning algorithms: Linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing (NLP): Transformer models, attention mechanisms, word embeddings Computer vision: Convolutional neural networks, recurrent neural networks, object detection Robotics: Reinforcement learning, motion planning, control systems Data ethics: Bias in machine learning, fairness in algorithms Your Profile Roles & Responsibilities: Technical Leadership: Lead a team of developers in the creation, implementation, and optimization of Generative AI solutions. Provide technical guidance, resolve challenges, and foster a collaborative environment. Prompt Engineering: Spearhead the design and development of prompt engineering strategies to influence and control the output of Generative AI models. Optimize prompts for desired results. Pipeline Design: Design end-to-end data pipelines that encompass data preprocessing, feature engineering, model training, and deployment. Ensure pipelines are efficient, scalable, and well-documented. Technical Review: Review the technical outputs generated by the team, including code, models, and pipelines. Ensure high-quality and maintainable solutions that adhere to best practices. Testing and Validation: Implement testing methodologies to validate the performance and accuracy of Generative AI models. Develop and execute unit tests, integration tests, and validation strategies. Deployment Strategy: Collaborate with DevOps and deployment teams to deploy trained models into production environments. Ensure smooth integration and monitor performance post-deployment. Workflow Optimization: Identify opportunities to optimize development workflows, enhance productivity, and streamline processes. Implement tools and practices to improve efficiency. Collaboration: Interface with cross-functional teams, including data scientists, architects, and business stakeholders. Collaborate on solution design, implementation, and project milestones. Documentation: Maintain comprehensive documentation of technical designs, code, and workflows. Ensure documentation is up-to-date, accessible, and understandable for team members.

Role & responsibilities We are seeking a skilled Data Engineer with advanced expertise in Python, PySpark, Databricks, and Machine Learning, along with a working knowledge of Generative and Agentic AI. This role is critical in ensuring data integrity and driving innovation across enterprise systems. You will design and implement ML-driven solutions to enhance Data Governance & Data Privacy initiatives through automation, self-service capabilities, and scalable, AI-enabled innovation. Key Responsibilities: Implement ML and Generative/Agentic AI solutions to optimize Data Governance processes. Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks. Develop automation frameworks to support data quality, lineage, classification, and access control. Develop and deploy machine learning models to uncover data patterns, detect anomalies, and enhance data governance and privacy compliance Collaborate with data stewards, analysts, and governance teams to build self-service data capabilities. Work with Databricks, Azure Data Lake, AWS, and other cloud-based data platforms for data engineering. Build, configure, and integrate APIs for seamless system interoperability. Ensure data integrity, consistency, and compliance across systems and workflows. Integrate AI models to support data discovery, metadata enrichment, and intelligent recommendations. Optimize data architecture to support analytics, reporting, and governance use cases. Monitor and improve the performance of ML/AI components in production environments. Stay updated with emerging AI and data engineering technologies to drive continuous innovation. Technical Skills: Strong programming skills in Python, PySpark, SQL for data processing and automation. Experience with Databricks and Snowflake (preferred) for building and maintaining data pipelines. Experience with Machine Learning model development and Generative/Agentic AI frameworks (e.g. LLMs, Transformers, LangChain) especially in the Data Management space Experience working with REST APIs & JSON for service integration Experience working with cloud-based platforms such as Azure, AWS, or GCP Power BI dashboard development experience is a plus. Soft Skills: Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities, with experience working across technical and business teams

Location: Any / Remote / Work From Home Employment Type: Full-time Job Summary: We are seeking skilled and innovative AI Engineers with a minimum 2-4 years of experience in developing and deploying AI solutions . The ideal candidate should have practical knowledge in AWS , Amazon Bedrock , LLMs , Claude AI , and Custom AI Development . You will contribute to the design and implementation of cutting-edge Generative AI (GenAI) and Mainstream AI applications across diverse business domains. This is an excellent opportunity to work with emerging technologies in an agile, fast-paced environment with full ownership of AI engineering pipelines. Key Responsibilities: Develop custom machine learning models and fine-tune foundation models for enterprise use Design and implement LLM-based and Generative AI solutions tailored to client use cases Work with OpenAI, Anthropic, HuggingFace models and their APIs to build secure, scalable AI systems Perform prompt engineering and experiment with parameter tuning and context optimization Build APIs and backend services to integrate AI models into product workflows Collaborate with product, data, and DevOps teams to deliver end-to-end AI-powered solutions Ensure best practices for AI model governance, security, performance, and ethical use Stay current with advancements in LLMs, vector databases (e.g., Pinecone, FAISS), and GenAI tooling Document architecture, experiments, and processes clearly and effectively Participate in peer reviews, client meetings, and cross-functional planning discussions Required Qualifications: Minimum 2-4 years of professional experience in AI/ML , with specific focus on LLMs and GenAI Strong experience working on AWS Bedrock , Lambda, and related services Proficiency in Python , including experience with libraries like HuggingFace, LangChain, etc. Familiarity with Anthropic , OpenAI , or other foundation models in production settings Experience with custom AI model development and model fine-tuning Good understanding of cloud-native AI deployments and API integrations Ability to apply prompt engineering techniques to optimize LLM responses Exposure to vector databases and RAG pipelines Strong problem-solving, communication, and team collaboration skills Preferred Qualifications (STRONG PLUS): Hands-on experience with LangChain, RAG pipelines, or agent frameworks Familiarity with AWS Sagemaker, DynamoDB, Lambda, or other AI tooling in AWS Knowledge of Docker or Kubernetes for containerizing AI workloads Understanding of MLOps principles and tools (MLflow, SageMaker Pipelines, etc.) Contributions to open-source AI projects or published GenAI applications AI/ML certifications Familiarity with enterprise use cases in biotech, healthcare, or manufacturing What We Offer: Remote work option Competitive salary package Exciting projects in the field of LLMs, AI, and cloud-native development Continuous learning opportunities in Generative AI and cloud AI tools A collaborative and fast-paced environment with a forward-thinking team Access to state-of-the-art tools and flexible project ownership How to Apply: Please submit your resume and cover letter outlining your relevant experience and why you'd be a great fit for Arocom. We differentiate candidates based on professionalism. We admire the new age methods like a video resume. If you have one please share the URL along with your resume. Your privacy is important to us, so we will not be contacting candidates by phone. If your application is selected, we will email you a link to schedule your interview at your convenient time. Please check your emails regularly, including your SPAM folder. Arocom encourages work from home and has a Bring Your Own Device (BYOD) policy. Employees / Consultants working from home are expected to use their personal laptops/desktops for work-related tasks.

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking an experienced 3+ years of IT experience ( 2 Years in AI/ML/DS Domain). Gen AI Development : Data collection and preparation: Collect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data, or creating synthetic data. Model development: Design and implement LLM models. This may involve choosing the right architecture, training the model, and tuning the hyperparameters. Model evaluation: Evaluate the performance of LLM models. This may involve measuring the accuracy of the model on a held-out dataset, or assessing the quality of the generated text. Model deployment: Deploy LLM models to production. This may involve packaging the model, creating a REST API, and deploying the model to a cloud computing platform. Responsible AI: Should have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives. Experience in working with ML toolkit like R, NumPy, MatLab etc.. Experience in data mining, statistical analysis and data visualization Your Profile Roles and Responsibility: LLM Development/Deployment Pipeline creation, workflows Study and transform Gen AI PoCs to production grade deployment Design machine learning systems, Run machine learning tests and experiments Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary

Responsibilities The Graphic Designer role for the Large Deals Business Narrative team integrates into a complex, strategic sales environment. In this role, Graphic Designers will support assigned activities under the guidance of a Lead Designer or Writer. Primary responsibilities include creating proposal response documents and presentations, marketing collateral, brand Identity packages, customized communication in both physical and digital formats, microsites, and multimedia elements such as video and audio recordings. Additionally, Graphic Designers are expected to engage in conceptualization activities, participate in strategy discussions, and attend team-wide enablement meetings. Responsibilities: Strong graphic design fundamentals (typography, color theory, hierarchy, contrast, and grid/alignments). Ability to abide by brand guidelines and possess a strong knowledge of design standards. Assist Lead Designers in the creation of various design projects throughout the entire project lifecycle. Enhance graphic visualization concepts based on guidance from Lead Designers to produce finalized artifacts. Capable of understanding specifics required to produce various presentation and design artifacts (dimensions, DPI, file size, etc.). Manage multiple concurrent assignments with defined timelines with the assistance of workload planning from Designer and Writer team leaders Demonstrate proficiency in designing PPT decks, brand identity, campaign branding, posters, booklets, handouts, emailers, sales videos, and animated PPTs for client meetings. Must Have skills: Demonstrate the ability to understand Large Deals sales activities and create plans from brainstorming ideas to the final execution of deliverables for assigned projects. Be present in-person with a team during critical activities for assigned projects. Exhibit strong teamwork and interpersonal skills, articulating ideas clearly during meetings to help non-creative stakeholders visualize concepts. Showcase problem-solving skills by presenting multiple solutions that communicate complex information clearly. Fluency in both spoken and written English is necessary to succeed in this role. Possess sound knowledge of design tools such as Adobe Photoshop, Illustrator, InDesign, Premiere, After Effects, and MS Office tools like PowerPoint and Word. Knowledge of additional design tools like 3D Studio Max or Generative AI is a bonus. Preferred Skills: Domain->Communication Design->Graphic Design Educational Requirements Bachelor of Arts Service Line Strategic Large Deals team * Location of posting is subject to business requirements

We are seeking a highly skilled Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will have a deep understanding of Machine Learning, AI, and cloud platforms like Azure. You will play a key role in designing, developing, and deploying ML models and Generative AI solutions to solve complex business problems. Role overview Engineering Masters degree or PhD in Data Science, Statistics, Mathematics, or related fields 5 years+ experience in a Machine Learning Engineer role into large corporate organizations Experience of working with ML models in a cloud ecosystem. Statistics & amp; Machine Learning Statistics : Strong understanding of statistical analysis and modelling techniques (e.g., regression analysis, hypothesis testing, time series analysis) Classical ML : Very strong knowledge in classical ML algorithms for regression & classification, supervised and unsupervised machine learning, both theoretical and practical (e.g. using scikit-learn, xgboost) ML niche : Expertise in at least one of the following ML specialisations: Timeseries forecasting / Natural Language Processing / Computer Vision Deep Learning: Good knowledge of Deep Learning fundamentals (CNN, RNN, transformer architecture, attention mechanism, ) and one of the deep learning frameworks (pytorch, tensorflow, keras) Generative A I: Good understanding of Generative AI specificities and previous experience in working with Large Language Models is a plus (e.g. with openai, langchain). MLOps Model strategy : Expertise in designing, implementing, and testing machine learning strategies. Model integration : Very strong skills in integrating a machine learning algorithm in a data science application in production. Model performance : Deep understanding of model performance evaluation metrics and existing libraries (e.g., scikit-learn, evidently) Model deployment: Experience in deploying and managing machine learning models in production either using specific cloud platform, model serving frameworks, or containerization. Model monitoring : Experience with model performance monitoring tools is a plus (Grafana, Prometheus). Software Engineering Python: Very strong coding skills in Python including modularity, OOP, data & config manipulation frameworks (e.g., pandas, pydantic) etc. Python ecosystem : Strong knowledge of tooling in Python ecosystem such as dependency management tooling (venv, poetry), documentation frameworks (e.g. sphinx, mkdocs, jupyter-book), testing frameworks (unittest,pytest) Software engineering practices: Experience in putting in place good software engineering practices such as design patterns, testing (unit, integration), clean code, code formatting etc. Debugging: Ability to troubleshoot and debug issues within machine learning pipelines. Data Science Experimentation and Analytics Data Visualization: Knowledge of data visualization tools such as plotly, seaborn, matplotlib, etc. to visualise, interpret and communicate the results of machine learning models to stakeholders. Basic knowledge of PowerBI is a plus. Data Cleaning: Experience with data cleaning and preprocessing techniques such as feature scaling, dimensionality reduction, and outlier detection (e.g. with pandas, scikit-learn). Data Science Experiments: Understanding of experimental design and A/B testing methodologies. Data Processing: Databricks/Spark: Basic knowledge of PySpark for big data processing Databases : Basic knowledge of SQL to query data in internal systems Data Formats: Familiarity with different data storage formats such as Parquet and Delta. DevOps Azure DevOps : Experience using a DevOps platform such as Azure DevOps for using Boards, Repositories, Pipelines Git : Experience working with code versioning (git), branch strategies, and collaborative work with pull requests. Proficient with the most basic git commands. CI / CD : Experience in implementing/maintaining pipelines for continuous integration (including execution of testing strategy) and continuous deployment is preferable. Cloud Platform: Azure Cloud: Previous experience with services like Azure Machine Learning Services and/or Azure Databricks on Azure is preferable. Soft skills: Strong analytical and problem-solving skills, with attention to detail Excellent verbal and written communication and pedagogical skills with technical and non-technical teams Excellent teamwork and collaboration skills Adaptability and reactivity to new technologies, tools, and techniques Fluent in English. What would you do here: Managing the lifecycle of machine learning models Develop and implement machine learning models to solve complex business problems. Ensure that models are accurate, efficient, reliable, and scalable. Deploy machine learning models to production environments, ensuring that models are integrated with software systems. Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly. Maintain machine learning models over time. This includes updating models as new data becomes available, retraining models to improve performance, and retiring models that are no longer effective. Develop and implement policies and procedures for ensuring the ethical and responsible use of machine learning models. This includes addressing issues related to bias, fairness, transparency, and accountability. Continuous Improvements: Stay up to date with the latest developments in the field: read research papers, attend conferences, and participate in trainings to expand their knowledge and skills. Identify and evaluate new technologies and tools that can improve the efficiency and effectiveness of machine learning projects. Propose and implement optimizations for current machine learning workflows and systems. Proactively identify areas of improvement within the pipelines. Make sure that created code is compliant with our set of engineering standards. Collaboration with other data experts (Data Engineers, Platform Engineers, and Data Analysts) Participate to pull requests reviews coming from other team members. Ask for review and comments when submitting their own work. Actively participate to the day-to-day life of the project (Agile rituals), the data science team (DS meeting) and the rest of the Global Engineering team.

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization . You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities 1) Technical Leadership Lead the technical design and architecture of complex Generative AI systems. Ensure solutions align with business objectives, scalability requirements, and technical feasibility. Guide development teams through best practices , architecture reviews, and technical decision-making processes. 2) Solution Architecture Design and develop end-to-end Generative AI solutions , including data pipelines , model training, deployment, and real-time monitoring. Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. Design, train, and fine-tune AI/ML models , especially Generative AI and Large Language Models (LLMs) , to address specific use cases. Build conversational AI solutions and chatbots using frameworks such as LangChain , RAG (Retrieval-Augmented Generation) , and Chain-of-Thought (COT) prompting . 3) Production Deployment Lead the deployment of Generative AI models into production environments . Optimize deployment pipelines leveraging tools like Docker, Kubernetes , and cloud-native services for orchestration. Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. 4) Data Processing & Feature Engineering Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. Implement data wrangling , preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Optimize workflows to extract meaningful insights from large datasets . 5) Model Optimization Identify and implement optimization strategies such as hyperparameter tuning , feature engineering , and model selection for performance enhancement. Focus on computational efficiency and scaling models to production-level performance. 6) Pilot/POCs Development Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. 7) Evangelization Promote and drive the adoption of Generative AI solutions across customer and delivery teams. Provide technical leadership and mentorship to teams working on GenAI projects. Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. 8) Continuous Improvement Stay at the forefront of AI advancements , frameworks, and tools, including emerging concepts in Generative AI. Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications 10+ years of experience in AI/ML architecture, model development, and production deployment Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions Hands-on experience with frameworks like LangChain , Retrieval-Augmented Generation (RAG) , and advanced prompting techniques Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting Experience working with cloud platforms , primarily GCP , with optional experience in AWS or Azure Strong understanding of MLOps tools, pipelines, and model monitoring in production Proficiency in Python and SQL for model development and data processing Experience with data preprocessing, ETL workflows , and feature engineering for AI applications Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions Experience working with large datasets for structured and unstructured AI applications Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies Proven track record of leading POCs/pilots and scaling them to production-grade deployments Preferred Skills Familiarity with Reinforcement Learning from Human Feedback (RLHF) . Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. Strong understanding of orchestration for large-scale production environments. Key Attributes Strong technical leadership and mentorship abilities. Excellent communication and stakeholder management skills. Strategic thinking with the ability to architect scalable and future-ready AI systems. Passion for solving business challenges using state-of-the-art AI techniques. Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us? Lead the development of cutting-edge Generative AI solutions for real-world applications. Be part of a collaborative, innovative, and technology-driven team. Opportunity to work with advanced AI/ML tools and frameworks. Drive innovation through technical leadership , mentorship, and solution evangelization. Continuous professional growth with access to the latest AI/ML technologies and frameworks.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance ParameterMeasure 1. Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created 2. Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation 3. Capability Building & Team Management% trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI.

The Role Machine learning and data science are interdisciplinary fields that require a combination of skills in mathematics, statistics, programming, and domain-specific knowledge to extract meaningful insights from data and develop predictive models. Skills Requirements Mandatory Skillset - ML Techniques, any ML Framework, Gen AI COncepts, Azure, Python Secondary Skillset - AWS, or Google Cloud Requirements Work closely with cross-functional teams to understand business requirements and translate them into machine learning solutions. Collect, clean, and pre-process large datasets to prepare them for machine learning models. Develop and implement machine learning algorithms and models for solving specific business problems. Collaborate with data engineers to ensure seamless integration of machine learning models into production systems. Fine-tune models for optimal performance and conduct thorough testing and validation. Stay updated on the latest advancements in machine learning and artificial intelligence and assess their potential impact on our projects. Effectively communicate complex technical concepts and findings to non-technical stakeholders. Monitor and maintain deployed models and update them as needed to adapt to changes in data or business requirements. Adhere to ethical standards and ensure that machine learning solutions comply with relevant regulations. Proficiency in Python with hands-on experience in cloud platforms including GCP, AWS, and Azure; strong skills in API integration.

Job description Looking for SDET/ Automation testing with Gen AI Testing Interested ones share CV and below details to snidafazli@altimetrik.com Name(as per aadhar card): Phone Number: EmailID: Current CTC: Fixed CTC: Expected CTC: holding any offers: Current Company: Payroll Company: Notice period: If serving Notice period, exact LWD: Current Location: Preferred location: Total years of experience: Relevant Experience below in years, SDET: Gen AI Testing: JAva: Selenium: API Automation: Rest Assured: BDD: Cucumber:

Senior AI & ML Platform Engineer Location: Bengaluru Experience Level: 3 to 10 Years About the Role We are building next-generation AI-powered platforms that leverage Large Language Models (LLMs), advanced Machine Learning (ML), NLP, and agentic workflows to automate critical business processes across multiple domains. We are looking for experienced AI/ML Engineers who are passionate about building real-world AI productsnot just experimenting. You will help design, prototype, and deploy intelligent systems integrating LLMs, agents, APIs, and robust ML models for classification, prediction, and optimization. Responsibilities Build and integrate agentic AI workflows using LangChain or similar frameworks. Develop APIs and backend services to support LLM and ML-driven platforms. Implement, train, and optimize lightweight and scalable ML models for classification, prediction, and anomaly detection. Work with LLMs (OpenAI, Claude, Gemini) to fine-tune prompts, create retrieval-augmented generation (RAG) systems, and chain multi-step tasks. Design and optimize vector search implementations for LLM-driven applications. Integrate AI models with external systems (VMS platforms, ERP systems) using APIs. Implement document processing pipelines combining OCR with LLM/ML validation. Apply ML techniques for supply-demand forecasting, fraud detection, and optimization. Participate in design discussions, brainstorming sessions, and agile sprints. Collaborate with senior AI architects and SMEs to refine platform capabilities. Required Skills Strong experience in Python for ML and AI development. Expertise in ML frameworks such as TensorFlow, PyTorch, scikit-learn. Knowledge of NLP tasks (text extraction, classification, summarization). Experience building and optimizing RAG workflows with vector databases. Solid understanding of API development (FastAPI, Flask, or similar frameworks). Familiarity with prompt engineering and agent orchestration concepts. Ability to build scalable ML models for classification, forecasting, and anomaly detection. Experience integrating ML solutions with cloud services (AWS, Azure, GCP). Knowledge of OCR tools and techniques for document processing. Exposure to multi-agent architectures and reinforcement learning is a plus. Understanding of feature engineering, model evaluation, and optimization techniques. Mindset We Are Looking For Builders mindset: You love turning ideas into working solutions fast. Curiosity: Passionate about keeping up with the latest in GenAI and ML. Problem-solver: Comfortable working in ambiguous environments where solutions need discovery, not just execution. Collaboration: Open to learning from senior architects and iterating based on feedback.

Job Title: AI Technical Lead Location: Bengaluru, work from Avaali office Employment Type: Full-time Reports to: CTO Key Responsibilities 1. Develop and Execute AI Initiatives Collaborate closely with business stakeholders at all levels to identify and implement AI-driven solutions that address key pain points and deliver measurable outcomes. Actively participate in multidisciplinary and cross-functional (fusion) teams to support the entire lifecycle of AI projectsfrom ideation to execution. Stay on top of cutting-edge AI trends, innovations, and best practices in the industry while leveraging these insights to deliver impactful solutions. 2. Design and Implement AI Solutions Architect AI-based solutions that align with Avaali's vision of operational cost optimization and margin improvement for clients. Ensure that all AI solutions are scalable, secure, governed, and adhere to applicable regulations and compliance standards. Create personalized solutions aligned with specific business requirements and ensure the delivery of high-quality outcomes. 3. Build and Scale the AI Practice in collaboration with the CTO Develop and implement standardized methodologies, frameworks, and best practices to drive consistency and excellence across AI initiatives. Create knowledge-sharing forums, training modules, and certifications to upskill internal teams and establish Avaali as a center of excellence for AI. This person would support the CTO in this area (he/she will be an important team member in this activity) Required Skills and Competencies Deep knowledge of AI/ML technologies, frameworks, and platforms, including hands-on experience with AI-based tools and cloud ecosystems. Strong expertise in designing enterprise-class AI systems that balance innovation with security, governance, and compliance needs. Proven track record of managing large-scale AI initiatives across industries, including successful implementation of impactful solutions. Outstanding analytical and problem-solving skills combined with a strategic mindset that embraces emerging opportunities. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees preferred. Minimum 8 years of experience including in AI leadership roles, ideally including consultancy or enterprise environments. Demonstrated success in building and scaling AI capabilities and teams. Experience defining and managing budgets for AI initiatives while delivering cost-effective outcomes. Benefits of Joining Avaali Be a key player in driving transformational change in cutting-edge industries. Work with a highly skilled and innovative team eager to push the boundaries of what AI can achieve. Opportunity to develop AI solutions with real-world impact, empowering businesses to thrive in a digital-first era. If you are ready to shape the future of AI at scale, we invite you to apply for this role.

Role & responsibilities Architect and implement AI/ML solutions tailored to client-specific business problems using Gen AI (e.g., LLMs like GPT, Gemini, Mistral) and traditional ML models (e.g., scikit-learn, XGBoost). Collaborate with client stakeholders to understand requirements, define problem statements, and translate them into scalable AI/ML solutions. Present demos and proof-of-concepts (POCs) to clients, showcasing the value of AI/ML in real-world scenarios Mentor and guide a cross-functional team of data scientists, ML engineers, and developers Drive best practices in model development, deployment, and monitoring Stay abreast of the latest advancements in Gen AI and ML, and evaluate their applicability to client use cases Contribute to internal knowledge bases and reusable solution accelerators Preferred candidate profile Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with Gen AI platforms and LLMs (e.g., OpenAI, Gemini, LLaMA, Mistral). Proven track record of deploying ML models in production environments (cloud/on-prem). Experience with API development, data pipelines, and dashboarding tools like Streamlit. Familiarity with DevOps and MLOps practices for model lifecycle management. Excellent communication and stakeholder management skills. Tools: LLM, SLM, Vector DB, Graph DB, Airflow, MLFlow, MLOps tools, NLP, KG, ML models (Regression, Clustering, Classification etc), LangChain, LangGraph, AutoGen

Job Description: Lead Solution Architect with experience in government programs preferred The candidate is expected to play the role of an expert level Technical Solution Architect in large programs The resource should mandatorily have minimum 10 Years experience in solution planning and system architecture designing with at least 5 years of experience as a Lead Architect for Analytical Systems The resource should have demonstrated extensive experience in the use of various techniques to develop robust data warehouse business intelligence AI solutions which have significant weightage to statistical and advanced analytics Key Responsibilities: ROLE AND RESPONSIBILITIES As a Principal Technical Solution Architect lead the engagement efforts at different stages from problem definition to diagnosis to solution design development deployment in large government implementation programs Create detailed design and architecture and process artifacts implement the solution and the deployment plan Connect with senior client business and IT stakeholders demonstrating thought leadership in domain process and technology Contribute to Unit and Organizational initiatives and COEs REQUIRED SKILLS AND EXPERIENCE Domain process functional technical Strong hands on and in depth knowledge of Data Analytics module Strong understanding of the Data Warehousing Business Intelligence AI solutions good understanding of airlines industry Thorough understanding of Agile methodologies Good understanding of business processes in the airlines domain or with government organizations Experience in leading and driving Business process workshops and Fit GAP analysis Should have working experience in a highly regulated environment Should be aware of release governance processes and have experience in working on any incident management tool Preferred Skills: Technology->Machine Learning->Generative AI,Technology->Machine Learning->AI/ML Solution Architecture and Design->traditional ai ml

7-10 years of experience in machine learning, deep learning. Experience End-to-end architecture design for machine learning solutions Deployment of AI models into scalable services Staying at the forefront of generative AI advancements Optimizing models for performance and scalability Collaborating with cross-functional teams for successful project delivery Degree in Computer Science, Information Technology, Electrical Engineering, or related field Experience or understanding of machine learning, deep learning, generative AIand MLOps Knowledge of deep learning techniques and frameworks (TensorFlow, PyTorch) Familiarity with cloud platforms, preferably Microsoft Azure A certification in AI or machine learning is advantageous Strong analytical and problem-solving skills Excellent communication and team collaboration abilities

Job Summary We are seeking highly skilled Sr. Backend Developers with an experience of 8 - 12 years to join our dynamic team. The ideal candidates should have strong expertise in Node.js , along with experience in Python, Generative AI (Gen AI) , and Natural Language Processing (NLP) preferred. Additionally, experience working with MongoDB, AWS Lambda, and cloud-based deployments is required. Key Responsibilities: Design, develop, and maintain scalable applications using Node.js and Python. Implement and optimize NLP models and Gen AI solutions for various applications. Develop and manage RESTful APIs and microservices using Node.js. Work with MongoDB for database management and optimization. Deploy and manage applications in AWS Lambda and other AWS services. Collaborate with cross-functional teams to integrate AI-driven solutions into the platform. Troubleshoot and debug applications, ensuring high availability and reliability. Required Skills & Experience: 8-12 years of hands-on experience in Backend Development using Node Js. Strong proficiency in Python, especially in AI/ML frameworks (TensorFlow, PyTorch, etc.). Experience working with Natural Language Processing (NLP) or Generative AI models. Proficiency in MongoDB, including database design and performance tuning. Hands-on experience with AWS Lambda and serverless architectures. Strong knowledge of REST APIs, GraphQL, and microservices. Experience with Docker, Kubernetes, and CI/CD pipelines is a plus. Ability to work in an Agile environment and collaborate with remote teams

What Your Responsibilities Will Be Lead and manage a team of AIML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AIML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AIML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI Machine Learning systems. Proficiency in programming languages relevant to AI ML, such as Python, R, Java, Scala, C++ and familiarity with AI ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing / ETL pipelines and visualization tools. General Qualifications Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies.

Experience working closely with other data scientists, data engineers' software engineers, data managers and business partners. 7+ years in designing, planning, prototyping, productionizing, maintaining knowledge in Python, Go, Java, SQL knowledge

Role Summary The Ecosystem Engineering Technology Engineer is responsible for guiding and supporting partners in embedding, sell-to, resell, and influence scenarios with IBM's strategic technologies. Activities include deal support with partners selling to clients and co-creating with partners (Joint Solutions, Assets, embedding of IBM technology). The Technology Engineer is part of a cross-functional team that delivers a unique co-creation experience for partners to accelerate and scale the embedding and use of IBM's strategic technologies to/in partner solutions. They use contemporary technologies and approaches to design, develop, test, and co-deliver solutions across the IBM Technology platform; They work closely with the Ecosystem Engineering: Solution Architect(s) to determine the feasibility of the solution and collaborate with the partner's and other Technology Engineers to implement a comprehensive solution. Ecosystem Technology Engineers are asked to specialize in a brand or set of capabilities to provide deep technical skills in their area of expertise. Required Education Bachelor's Degree Preferred Education Bachelor's Degree Required Technical and Professional Expertise Expert level knowledge in IBM Business Automation suite of products (CP4BA - RPA, BPM - BAW, Process Mining, FileNet) . Very good understanding of Generative AI (IBM watsonx platform or equivalent) . Hands-on coding experience in Python, Java, Node.js, JavaScript, React . Agentic AI framework will be an added advantage. Excellent communication and presentation skills.

Your role and responsibilities Back end development with GoLang Expertise in Kubernetes/OpenShift, Cloud service providers. Knowledge of Generative AI, and ability to integrate AI to applications. Ability to pick up new areas based on business requirements Excellent communication skills Required education Bachelor's Degree Required technical and professional expertise 6+ years of overall experience in backend development. Excellent understanding of system design and best practices. 6+ years of application development with GoLang development. Good level of expertise in Kubernetes or OpenShift, use of Docker/Podman and Cloud service providers. Good level of knowledge of CNI, container native storage. Expertise in Version Control - Git Experience using cloud technologies (AWS/GCP/Azure/IBM Cloud) Experience with Ansible and Shell scripting Proficient in Linux administration. Experience of IaC (Terraform) Expertise in Version Control - Git Design functional DevOps application lifecycle. Good understanding of CICD pipelines such as Jenkins. Should have hands-on in writing and debugging Jenkinsfile Experience using build tools such as Maven, Gradle, Make, Ant Knowledge of AI - Pytorch, TensorFlow, Scikit,Generative AI, and ability to integrate AI functionalities to applications. ABOUT BUSINESS UNIT IBM Systems helps IT leaders think differently about their infrastructure. IBM servers and storage are no longer inanimate - they can understand, reason, and learn so our clients can innovate while avoiding IT issues. Our systems power the world's most important industries and our clients are the architects of the future.Join us to help build our leading-edge technology portfoliodesigned for cognitive business and optimized for cloud computing.