93 Vertex Ai Jobs - Page 4

Role: Solution Architect (AI/ML Specialization) Full time Professional About Onix : Onix is a Google Cloud Premier Partner serving over 1,400 customers, including several of the world's largest corporations, enabling them to effectively leverage Google Cloud Platform across industries and use cases. Onix specialises in Google Cloud Solutions such as generative AI, workload migrations, data & analytics, data infrastructure and visualisation, infrastructure services, application modernisation, collaboration & productivity, and location-based services. Onix is a 12-time Google Partner of the Year award winner and a Google Cloud Managed Services Partner. Summary: We are seeking a skilled and customer-focused AI/ML Solution Architect to join Onixs Solution Engineering team. This role blends deep technical expertise with presales acumen to architect, evangelise, and deliver cutting-edge AI and ML solutions on GCP and multi-cloud platforms. You will engage directly with clients in high-impact discussions, guiding them through the art of the possible with generative AI, MLOps, and cloud-native tools. As a key technical advisor, you will participate in strategic discovery sessions, lead solution ideation and architecture reviews , and collaborate closely with clients, sales, and engineering teams to shape transformational AI/ML initiatives. Your insights will help drive client success, showcase technical feasibility , and demonstrate business value through proofs of concept and impactful solution designs. Key Responsibilities: Partner with sales and customer engineering teams in presales engagements to identify AI/ML opportunities and craft tailored solution architectures. Design scalable, cloud-native AI/ML solutions primarily on Google Cloud Platform (GCP) leveraging tools like Vertex AI, LangChain, OpenAI APIs, and MLOps frameworks . Lead technical workshops, client demos, and architecture sessions to articulate value, drive alignment, and win stakeholder confidence. Review solution proposals across teams to ensure architectural integrity, scalability, and adherence to best practices . Stay ahead of the curve by assessing emerging GenAI tools and frameworks to validate new ideas and accelerate innovation . Required Qualifications: Bachelors degree in Computer Science, Engineering, or a related field; Master’s degree preferred. Extensive hands-on experience with cloud platforms , especially GCP (AWS and Azure exposure is a plus). Strong understanding of AI/ML tools and systems , including TensorFlow, PyTorch, Vertex AI, OpenAI, LangChain , and MLOps pipelines . 4–5 years of experience in data science, software development, or machine learning , with proficiency in languages like Python, Java, or JavaScript. Proven experience applying ML technologies to real-world industry use cases , with a solid grasp of data lifecycle and cloud deployment strategies. Exceptional client-facing communication and solution storytelling skills , with a track record in technical presales or consulting roles .

Role & responsibilities : Job Title : AI Engineer (AI-Powered Agents, Knowledge Graphs, & MLOps) Location: Hyderabad Job Type : Full-time Hands-on Gen AI development in GCP and Azure stack Job Summary : We seek an AI Engineer with deep expertise in building AI-powered agents, designing and implementing knowledge graphs, and optimizing business processes through AI-driven solutions. The role also requires hands-on experience in AI Operations (AI Ops), including continuous integration/deployment (CI/CD), model monitoring, and retraining. The ideal candidate will have experience working with open-source or commercial large language models (LLMs) and be proficient in using platforms like Azure Machine Learning Studio or Google Vertex AI to scale AI solutions effectively. Key Responsibilities : AI Agent Development : Design, build, and deploy AI-powered agents for applications such as virtual assistants, customer service bots, and task automation systems using LLMs and other AI models. Knowledge Graph Implementation : Develop and implement knowledge graphs for enterprise data integration, enhancing the retrieval, structuring, and management of large datasets to support decision-making. AI-Driven Process Optimization : Collaborate with business units to optimize workflows using AI-driven solutions, automating decision-making processes and improving operational efficiency. AI Ops (MLOps) : Implement robust AI/ML pipelines that follow CI/CD best practices to ensure continuous integration and deployment of AI models across different environments. Model Monitoring and Maintenance : Establish processes for real-time model monitoring, including tracking performance, drift detection, and accuracy of models in production environments. Model Retraining and Optimization : Develop automated or semi-automated pipelines for model retraining based on changes in data patterns or model performance. Implement processes to ensure continuous improvement and accuracy of AI solutions. Cloud and ML Platforms : Utilize platforms such as Azure Machine Learning Studio, Google Vertex AI, and open-source frameworks for end-to-end model development, deployment, and monitoring. Collaboration : Work closely with data scientists, software engineers, and business stakeholders to deploy scalable AI solutions that deliver business impact. MLOps Tools : Leverage MLOps tools for version control, model deployment, monitoring, and automated retraining processes to ensure operational stability and scalability of AI systems. Performance Optimization : Continuously optimize models for scalability and performance, identifying bottlenecks and improving efficiencies. Qualifications : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3+ years of experience as an AI Engineer, focusing on AI-powered agent development, knowledge graphs, AI-driven process optimization, and MLOps practices. Proficiency in working with large language models (LLMs) such as GPT-3/4, GPT-J, BLOOM, or similar, including both open-source and commercial variants. Experience with knowledge graph technologies, including ontology design and graph databases (e.g., Neo4j, AWS Neptune). AI Ops/MLOps Expertise : Hands-on experience with AI/ML CI/CD pipelines, automated model deployment, and continuous model monitoring in production environments. Familiarity with tools and frameworks for model lifecycle management, such as MLflow, Kubeflow, or similar. Strong skills in Python, Java, or similar languages, and proficiency in building, deploying, and monitoring AI models. Solid experience in natural language processing (NLP) techniques, including building conversational AI, entity recognition, and text generation models. Model Monitoring & Retraining : Expertise in setting up automated pipelines for model retraining, monitoring for drift, and ensuring the continuous performance of deployed models. Experience in using cloud platforms like Azure Machine Learning Studio, Google Vertex AI, or similar cloud-based AI/ML tools. Preferred Skills : Experience with building or integrating conversational AI agents using platforms like Microsoft Bot Framework, Rasa, or Dialogflow. Familiarity with AI-driven business process automation and RPA integration using AI/ML models. Knowledge of advanced AI-driven process optimization tools and techniques, including AI orchestration for enterprise workflows. Experience with containerization technologies (e.g., Docker, Kubernetes) to support scalable AI/ML model deployment. Certification in Azure AI Engineer Associate, Google Professional Machine Learning Engineer, or relevant MLOps-related certifications is a plus. Preferred candidate profile Perks and benefits

job position - vertex AI support engineer experience -- 5 - 9 Years location - Bangalore ( relocation candidate also can apply ) notice period - only immediate joiner can apply ( only serving notice period max - 20 June 2025 ) shift - rotational shift employment type - permanents with brainworks business solution mandatory skills - Vertex AI , Python ,GCP services - , ML/AI -, SQL interested candidate please share your CV's on rutuja.s@bwbsol.com / 9850368787

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle

We specialize in delivering high-quality human-curated data and AI-first scaled operations services Based in San Francisco and Hyderabad, we are a fast-moving team on a mission to build AI for Good, driving innovation and societal impact Role Overview: We are looking for a Data Scientist to join and build intelligent, data-driven solutions for our client that enable impactful decisions This role requires contributions across the data science lifecycle from data wrangling and exploratory analysis to building and deploying machine learning models Whether youre just getting started or have years of experience, were looking for individuals who are curious, analytical, and driven to make a difference with data Responsibilities: Design, develop, and deploy machine learning models and analytical solutions Conduct exploratory data analysis and feature engineering Own or contribute to the end-to-end data science pipeline: data cleaning, modeling, validation, and deployment Collaborate with cross-functional teams (engineering, product, business) to define problems and deliver measurable impact Translate business challenges into data science problems and communicate findings clearly Implement A/B tests, statistical tests, and experimentation strategies Support model monitoring, versioning, and continuous improvement in production environments Evaluate new tools, frameworks, and best practices to improve model accuracy and scalability Required Skills: Strong programming skills in Python including libraries such as pandas, NumPy, scikit-learn, matplotlib, seaborn Proficient in SQL, comfortable querying large, complex datasets Sound understanding of statistics, machine learning algorithms, and data modeling Experience building end-to-end ML pipelines Exposure to or hands-on experience with model deployment tools like FastAPI, Flask, MLflow Experience with data visualization and insight communication Familiarity with version control tools (eg, Git) and collaborative workflows Ability to write clean, modular code and document processes clearly Nice to Have: Experience with deep learning frameworks like TensorFlow or PyTorch Familiarity with data engineering tools like Apache Spark, Kafka, Airflow, dbt Exposure to MLOps practices and managing models in production environments Working knowledge of cloud platforms like AWS, GCP, or Azure (e, SageMaker, BigQuery, Vertex AI) Experience designing and interpreting A/B tests or causal inference models Prior experience in high-growth startups or cross-functional leadership roles Educational Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Engineering, or a related field Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,India

In this role, you will drive the end-to-end development and deployment of AI/ML solutions on Cloud, applying your expertise in machine learning, MLOps, and GenAI. You will mentor junior engineers by establishing best practices and guiding solution design. Additionally, you will design, implement, and optimize advanced machine learning algorithms using robust data science techniques, while driving the scaling and adoption of AI/ML technologies to meet strategic business objectives. If you have a passion for AI, cloud-based ML solutions, and driving scalable innovation, this role is for you. You have: Bachelors or masters degree in computer science, Engineering, or related field with 8+ years of experience in machine learning, data science, and statistics. Expertise in ML algorithms with strong Python and SQL skills, including Jupyter notebooks. Proven knowledge of GenAI and Agentic AI technologies. Hands-on experience with MLOps tools like Kubeflow, Vertex AI, and GenAI/LLMops. Grip on, Kubernetes, Docker, and microservices architecture. It would be nice if you also had: Experience with OpenAI, Llama, and Lang Chain frameworks. Practical experience in Pytest and Rust programming. Prior experience developing AI applications in the telecom domain. Google Cloud Professional Machine Learning Engineer certification. Architect and develop AI/ML use cases on Cloud, driving projects from discovery and proof of concept through industrialization, deployment, and ongoing maintenance. Mentor and guide junior engineers in defining robust methodologies and evaluating the most effective technical solutions. Propose, implement, test, and select optimal machine learning algorithms by leveraging advanced statistical tools and data science techniques to uncover insights and generate accurate predictions. Drive the rapid scaling and integration of AI and ML technologies to enhance system performance and support strategic business objectives.

Job Description About Onix We a trusted cloud consulting company and leading Google Cloud partner that helps companies get the most out of their technology with cloud-powered solutions, best-in-class services, and the data migration products that unleash AI potential. We are able to deliver exceptional results for our customers because of our 20+ year partnership with Google Cloud, depth of technology expertise, and IP-driven data and AI solutions. We offer solutions across a wide range of use cases and industries that are tailored to the unique needs of each customer. From advanced cloud security solutions to innovative AI capabilities and data migration products, we have you covered. Our global team of experts are the most reliable, talented and knowledgeable in the industry. About the Role We are seeking an experienced AI/ML professional 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. Required Skills & Qualifications 7+ 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.

Job Description: We are seeking experienced Python developers with hands-on expertise in Google Cloud Vertex AI. The ideal candidate will have a strong background in machine learning model development, deployment pipelines, and cloud-native applications. Key Skills: Advanced proficiency in Python Experience with Vertex AI (training, deployment, pipelines, model registry) Familiarity with Google Cloud Platform (GCP) services like BigQuery, Cloud Functions, AI Platform Understanding of ML lifecycle, including data preprocessing, training, evaluation, and monitoring CI/CD experience with ML workflows (e.g., Kubeflow, TFX, or Vertex Pipelines) Preferred: Experience integrating Vertex AI with DBT, Airflow, or Looker Exposure to MLOps and model governance

Your future duties and responsibilities: Skill: pgvector,Vertex AI, FastAPI, Flask, Kubernetes Develops and optimizes AI applications for production, ensuring seamless integration with enterprise systems and front-end applications. Builds scalable API layers and microservices using FastAPI, Flask, Docker, and Kubernetes to serve AI models in real-world environments Implements and maintains AI pipelines with MLOps best practices, leveraging tools like Azure ML, Databricks, AWS SageMaker, and Vertex AI Ensures high availability, reliability, and performance of AI systems through rigorous testing, monitoring, and optimization Works with agentic frameworks such as LangChain, LangGraph, and AutoGen to build adaptive AI agents and workflows Experience with GCP, AWS, or Azure - utilizing services such as Vertex AI, Bedrock, or Azure Open AI model endpoints Hands on experience with vector databases such as pgvector, Milvus, Azure Search, AWS OpenSearch, and embedding models such as Ada, Titan, etc. Collaborates with architects and scientists to transition AI models from research to fully functional, high-performance production systems. Skills: Azure Search Flask Kubernetes

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Principal Consultant - Lead Solution Architect, Google Cloud Platform Pre-Sales - Data & AI About Genpact: Genpact (NYSE: G) is a global professional services firm delivering outcomes that transform businesses. With a proud 25-year history and over 125,000 diverse professionals in 30+ countries, we are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for our clients. We serve leading global enterprises, including the Fortune Global 500, leveraging our deep industry expertise , digital innovation, and cutting-edge capabilities in data, technology, and AI. Join our vibrant team in India to shape the future of business through intelligent operations and drive meaningful impact. The Opportunity: Genpact India is expanding its Google Cloud Platform (GCP) capabilities and seeking a highly experienced and technically astute Senior Principal Consultant / Lead Solution Architect specializing in Data and Artificial Intelligence. This critical role will be at the forefront of Genpact%27s growth in the GCP ecosystem in India and globally, leading complex pre-sales engagements, designing transformative data and AI solutions, and fostering strong client relationships. You will operate as a trusted advisor, translating intricate client challenges into compelling, implementable solutions on Google Cloud. Responsibilities: Solution Architecture & Design Leadership: Lead the technical pre-sales process for complex data and AI opportunities on Google Cloud Platform / AWS / Azure (any 2) from initial discovery through to proposal and Statement of Work (SOW) development. Design and articulate highly scalable, secure, and resilient enterprise-grade data and AI architectures leveraging a wide array of GCP services / AWS / Azure services. (any 2) Client Engagement & Advisory: Engage deeply with prospective clients%27 senior IT and business stakeholders, including CXOs, to understand their strategic objectives , critical business challenges, and existing data landscape. Position Genpact%27s GCP / AWS / Azure Data & AI offerings as key enablers for their digital transformation journey. Technical Demonstrations & Workshops: Conduct impactful technical presentations, deep-dive workshops, and product demonstrations (including Proof-of-Concepts where required ) tailored to specific client needs, showcasing the advanced capabilities of GCP / AWS / Azure Data & AI services and Genpact%27s differentiated value. Proposal Development & Commercial Support: Take ownership of the technical sections of proposals, RFPs, and SOWs, ensuring accuracy, technical feasibility, clear value articulation, and alignment with Genpact%27s delivery capabilities. Provide robust technical estimation and sizing for proposed solutions. Sales & Delivery Collaboration: Partner closely with Genpact%27s sales teams to drive deal progression, providing technical guidance, competitive intelligence, and effective solution positioning. Collaborate with delivery teams to ensure proposed solutions are executable, scalable, and align with Genpact%27s operational excellence standards. Technology & Market Expertise: Maintain expert-level knowledge of the latest trends, services, and product roadmaps in Google Cloud Platform, AWS / Azure (any two) , Data Engineering, Machine Learning, Artificial Intelligence (including Generative AI), and relevant industry best practices. Thought Leadership & IP Contribution: Contribute to Genpact%27s intellectual property by developing reusable assets, solution accelerators, and participating in internal/external knowledge sharing, including whitepapers, blogs, and industry events. Mentorship & Capability Building: Mentor and guide junior architects and data engineers within the team, fostering a culture of technical excellence and continuous learning in Google Cloud Data & AI. Qualifications we seek in you! Minimum Qualifications progressive experience in technical roles within data analytics, data warehousing, business intelligence, machine learning, and artificial intelligence, with a significant portion in a client-facing pre-sales, solution architecture, or consulting capacity . hands-on experience architecting, designing, and delivering complex data and AI solutions on Google Cloud Platform. Deep and demonstrable expertise across the Google Cloud Data & AI stack: Core Data Services: BigQuery , Dataflow, Dataproc , Pub/Sub, Cloud Storage, Cloud SQL, Cloud Spanner, Composer, Data Catalog, Dataplex. AI/ML Services: Vertex AI (including MLOps , Workbench, Training, Prediction, Explainable AI), Generative AI offerings (e.g., Gemini, Imagen), Natural Language API, Vision AI, Speech-to-Text, Dialogflow , Recommendation AI. BI & Visualization: Looker, Data Studio. Similar to above Google Cloud stack, need to have exposure to one other cloud data stack - either AWS or Azure Proven experience in translating complex business challenges into viable , scalable technical solutions on GCP, articulated with clear business value. Exceptional communication, presentation, and interpersonal skills, with the ability to engage, influence, and build rapport with diverse audiences from technical teams to senior business executives. Strong problem-solving, analytical, and strategic thinking abilities, with a commercial mindset. Experience in leading and contributing to large, complex deal pursuits in a competitive environment. Bachelor%27s degree in Computer Science , Engineering, or a related technical field. Master%27s degree preferred. Google Cloud Professional Certifications are highly preferred (e.g., Professional Cloud Architect, Professional Data Engineer, Professional Machine Learning Engineer). Ability to travel to client sites within India and potentially internationally as required . Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Experienced Dialogflow CX & Generative AI candidate to design, develop, and optimize AI-driven conversational solutions. The ideal candidate will have expertise in Dialogflow CX, Conversational AI, and Generative AI technologies. Required Skills & Qualifications: Hands-on experience with Dialogflow CX and Conversational AI platforms. Strong knowledge of NLP, AI, and ML techniques. Experience working with Generative AI models (e.g., Vertex.ai, Gemini , GPT, BERT, etc.). Proficiency in Google Cloud, Python, APIs, and AI-driven automation. Ability to design complex conversational workflows with intents, contexts, and entities. Experience integrating AI chatbots with various platforms and third-party services. Key Responsibilities: Develop and optimize chatbot/voicebot solutions using Google Dialogflow CX. Design conversational flows with advanced NLP techniques for natural and effective communication. Integrate Generative AI models to enhance the chatbot's ability to generate human-like responses. Fine-tune AI models for accuracy, efficiency, and improved user experience. Collaborate with cross-functional teams to ensure smooth implementation and functionality. Monitor, analyze, and improve chatbot/voicebot performance using data insights and user feedback. Stay updated with the latest advancements in Conversational AI & GenAI technologies.

We are seeking a hands-on Lead Data Engineer to drive the design and delivery of scalable, secure data platforms on Google Cloud Platform (GCP). In this role you will own architectural decisions, guide service selection, and embed best practices across data engineering, security, and performance disciplines. You will partner with data modelers, analysts, security teams, and product owners to ensure our pipelines and datasets serve analytical, operational, and AI/ML workloads with reliability and cost efficiency. Familiarity with Microsoft Azure data services (Data Factory, Databricks, Synapse, Fabric) is valuable, as many existing workloads will transition from Azure to GCP. Key Responsibilities Lead end-to-end development of high-throughput, low-latency data pipelines and lake-house solutions on GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Dataplex, etc.). Define reference architectures, technology standards for data ingestion, transformation, and storage. Drive service-selection trade-offscost, performance, scalability, and securityacross streaming and batch workloads. Conduct design reviews and performance tuning sessions; ensure adherence to partitioning, clustering, and query-optimization standards in BigQuery. Contribute to long-term cloud data strategy, evaluating emerging GCP features and multi-cloud patterns (Azure Synapse, Data Factory, Purview, etc.) for future adoption. Lead the code reviews and oversee the development activities delegated to Data engineers. Implement best practices recommended by Google Cloud Provide effort estimates for the data engineering activities Participate in discussions to migrate existing Azure workloads to GCP, provide solutions to migrate the work loads for selected data pipelines Must-Have Skills 810 years in data engineering, with 3+ years leading teams or projects on GCP. Expert in GCP data services (BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, Cloud Storage) and orchestration with Cloud Composer or Airflow. Proven track record designing and optimizing large-scale ETL/ELT pipelines (streaming + batch). Strong fluency in SQL and one major programming language (Python, Java, or Scala). Deep understanding of data lake / lakehouse, dimensional & data-vault modeling, and data governance frameworks. Excellent communication and stakeholder-management skills; able to translate complex technical topics to non-technical audiences. Nice-to-Have Skills Hands-on experience with Microsoft Azure data services (Azure Synapse Analytics, Data Factory, Event Hub, Purview). Experience integrating ML pipelines (Vertex AI, Dataproc ML) or real-time analytics (BigQuery BI Engine, Looker). Familiarity with open-source observability stacks (Prometheus, Grafana) and FinOps tooling for cloud cost optimization. Preferred Certifications Google Professional Data Engineer (strongly preferred) or Google Professional Cloud Architect Microsoft Certified: Azure Data Engineer Associate (nice to have) Education Bachelors or Masters degree in Computer Science, Information Systems, Engineering, or a related technical field. Equivalent professional experience will be considered.

We are seeking a highly skilled, hands-on Machine Learning Engineer/Data Scientist with a robust background in developing, coding, and deploying advanced ML models. The ideal candidate will have demonstrable expertise in computer vision, object detection, object tracking, and NLP, with a proven track record of writing production-grade code and developing state-of-the-art models to solve complex business challenges. Key Responsibilities: End-to-End ML Pipeline Development: Design, code, test, and deploy robust machine learning pipelinesfrom data collection and preprocessing to model training and production deployment. Computer Vision & Object Detection: Develop and fine-tune algorithms for computer vision applications using tools like Ultralytics YOLO and OpenCV, with hands-on experience in object detection and object tracking. NLP Model Development: Build and optimize NLP models for tasks such as text analysis, sentiment analysis, and language processing using frameworks like Hugging Face Transformers or spaCy. Cloud-Based Model Deployment: Utilize Google Cloud services, particularly Vertex AI, for scalable model development, training, testing, and deployment. Code Quality & Optimization: Write clean, modular, and efficient code; perform debugging, code reviews, and performance tuning to ensure scalable and maintainable codebases. Collaboration & Integration: Work closely with data engineering and software development teams to integrate ML models into production environments and ensure seamless deployment. Continuous Improvement: Stay up-to-date with the latest advancements in machine learning and AI, integrating new technologies and methods as appropriate. Documentation & Best Practices: Maintain thorough documentation of code, methodologies, and experiments, adhering to industry best practices and MLOps principles. Required Skills and Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. 5+ years of professional experience in data science and machine learning with a strong emphasis on hands-on coding and model development. Advanced proficiency in Python, and extensive experience with ML libraries and frameworks such as TensorFlow, PyTorch, OpenCV, and Ultralytics YOLO. Demonstrable expertise in developing and deploying computer vision models (object detection and tracking) and NLP solutions. Hands-on experience with cloud platforms, especially Google Cloud (Vertex AI), for scalable ML model training and deployment. Strong analytical, debugging, and performance optimization skills, with a commitment to high-quality code and software engineering best practices. Familiarity with data annotation platforms (e.g., Roboflow) and experience in integrating these into model development workflows. Excellent communication and collaboration skills to work effectively in cross-functional teams. Preferred Skills: Experience with MLOps practices and CI/CD pipelines for machine learning. Familiarity with big data technologies and distributed computing frameworks. Contributions to open-source projects or publications in relevant fields. Expertise in model interpretability, monitoring, and performance tuning in production environments. (Hands-On Coding & Model Development)

We are seeking a highly skilled, hands-on Machine Learning Engineer/Data Scientist with a robust background in developing, coding, and deploying advanced ML models. The ideal candidate will have demonstrable expertise in computer vision, object detection, object tracking, and NLP, with a proven track record of writing production-grade code and developing state-of-the-art models to solve complex business challenges. Key Responsibilities: End-to-End ML Pipeline Development: Design, code, test, and deploy robust machine learning pipelinesfrom data collection and preprocessing to model training and production deployment. Computer Vision & Object Detection: Develop and fine-tune algorithms for computer vision applications using tools like Ultralytics YOLO and OpenCV, with hands-on experience in object detection and object tracking. NLP Model Development: Build and optimize NLP models for tasks such as text analysis, sentiment analysis, and language processing using frameworks like Hugging Face Transformers or spaCy. Cloud-Based Model Deployment: Utilize Google Cloud services, particularly Vertex AI, for scalable model development, training, testing, and deployment. Code Quality & Optimization: Write clean, modular, and efficient code; perform debugging, code reviews, and performance tuning to ensure scalable and maintainable codebases. Collaboration & Integration: Work closely with data engineering and software development teams to integrate ML models into production environments and ensure seamless deployment. Continuous Improvement: Stay up-to-date with the latest advancements in machine learning and AI, integrating new technologies and methods as appropriate. Documentation & Best Practices: Maintain thorough documentation of code, methodologies, and experiments, adhering to industry best practices and MLOps principles.Required Skills and Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. 5+ years of professional experience in data science and machine learning with a strong emphasis on hands-on coding and model development. Advanced proficiency in Python, and extensive experience with ML libraries and frameworks such as TensorFlow, PyTorch, OpenCV, and Ultralytics YOLO. Demonstrable expertise in developing and deploying computer vision models (object detection and tracking) and NLP solutions. Hands-on experience with cloud platforms, especially Google Cloud (Vertex AI), for scalable ML model training and deployment. Strong analytical, debugging, and performance optimization skills, with a commitment to high-quality code and software engineering best practices. Familiarity with data annotation platforms (e.g., Roboflow) and experience in integrating these into model development workflows. Excellent communication and collaboration skills to work effectively in cross-functional teams. Preferred Skills: Experience with MLOps practices and CI/CD pipelines for machine learning. Familiarity with big data technologies and distributed computing frameworks. Contributions to open-source projects or publications in relevant fields. Expertise in model interpretability, monitoring, and performance tuning in production environments.

We are looking for IBMi trained resources with Google Cloud Platform or Vertex AI as freshers to start working with us. 1st year they will be with as 'TRAINEE' and will be working in 3 different shifts. We will train them in our Product, Managed Services, development based on our standards. If they are successful we will confirm their employment. Role & responsibilities Preferred candidate profile

!!Mega Walk In Drive!! Hiring Data Scientist (Walk In Interview) 4D Global Medical Billing Services Minimum 2 years of Experience in data science, machine learning, and AI model training. Strong skills in Python, TensorFlow, Hugging Face Transformers, and Google Vertex AI. Prior experience in RCM, healthcare data, or insurance analytics is a strong plus. CONTACT PERSON - HR Lissy(9952221050)HR Sneha(9344656213)HR Naveen(6381271323)

Designation: AI/ML Engineer Experience : 2 - 5 years exp Education : Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related fields Job Location: Navi Mumbai (Onsite) Role. Key Responsibilities: Design and develop AI/ML models for OCR, focusing on handwritten, printed, and multi-language documents. Train and fine-tune custom OCR models using frameworks like TensorFlow, PyTorch, or Google Vertex AI, etc. Integrate OCR solutions into a browser-based platform using Node.js (backend) and React.js (frontend). Preprocess and analyze scanned or photographed documents to improve text recognition accuracy using tools like OpenCV. Evaluate and compare third-party OCR services (e.g., Google Vision, Azure OCR, Amazon Textract). Build intelligent data pipelines for document parsing, classification, and information extraction. Collaborate with full-stack developers to deploy AI models into production web apps. Keep up to date with advancements in AI tools, OCR technologies, and web integration strategies. Experience in diagram or symbol detection Required Skills & Qualifications:* Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related fields 3+ years of proven experience with OCR technologies and document image processing Strong proficiency in Python for model development, training, and data pipelines Working knowledge of JavaScript, Node.js, and React.js for full-stack AI integration Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, or similar) Demonstrated ability to preprocess and enhance document images using OpenCV or similar tools. Experience deploying ML models to production environments. Familiarity with version control (Git), containerization (Docker), and cloud services (AWS/GCP/Azure) *Good to Have Skills:* Experience with Agentic AI frameworks (LangChain, AutoGPT, or similar) Knowledge of RAG (Retrieval-Augmented Generation) architectures for document context Familiarity with LLM integration for enhanced document understanding Experience with multi-language document processing and non-Latin character recognition Understanding of diagram, table, and technical symbol detection in documents Background in MLOps tools (MLflow, DVC, Vertex AI) for model lifecycle management Experience developing autonomous AI agents for document processing automation Familiarity with prompt engineering for specialized OCR applications Interested candidate can apply there resume on email id :- hr@techplusinfotech.com .

ML/AL Gen AI Expert - Vertex AI on Google Cloud and MLOps . • GenAI tools & APIs with PaLM, Gemini, LLM ,Vertex Ai • Python Scripting scikit-learn, TensorFlow, PyTorch, LangChain. • GCP services •media domain (OTT, DTH, Web)