33 Vertex Ai Jobs

Strong in Python with libraries such as polars, pandas, numpy, scikit-learn, matplotlib, tensorflow, torch, transformers • Must have: Deep understanding of modern recommendation systems including two-tower , multi-tower , and cross-encoder architectures • Must have: Hands-on experience with deep learning for recommender systems using TensorFlow , Keras , or PyTorch • Must have: Experience generating and using text and image embeddings (e.g., CLIP , ViT , BERT , Sentence Transformers ) for content-based recommendations • Must have: Experience with semantic similarity search and vector retrieval for matching user-item representations • Must have: Proficiency in building embedding-based retrieval models , ANN search , and re-ranking strategies • Must have: Strong understanding of user modeling , item representations , temporal/contextual personalization • Must have: Experience with Vertex AI for training, tuning, deployment, and pipeline orchestration • Must have: Experience designing and deploying machine learning pipelines on Kubernetes (e.g., using Kubeflow Pipelines , Kubeflow on GKE , or custom Kubernetes orchestration ) • Should have experience with Vertex AI Matching Engine or deploying Qdrant , F AISS , ScaNN , on GCP for large-scale retrieval • Should have experience working with Dataproc (Spark/PySpark) for feature extraction, large-scale data prep, and batch scoring • Should have a strong grasp of cold-start problem solving using metadata and multi-modal embeddings • Good to have: Familiarity with Multi-Modal Retrieval Models combining text, image, and tabular features • Good to have: Experience building ranking models (e.g., XGBoost , LightGBM , DLRM ) for candidate re-ranking • Must have: Knowledge of recommender metrics (Recall@K, nDCG, HitRate, MAP) and offline evaluation frameworks • Must have: Experience running A/B tests and interpreting results for model impact • Should be familiar with real-time inference using Vertex AI , Cloud Run , or TF Serving • Should understand feature store concepts , embedding versioning , and serving pipelines • Good to have: Experience with streaming ingestion (Pub/Sub, Dataflow) for updating models or embeddings in near real-time • Good to have: Exposure to LLM-powered ranking or personalization , or hybrid recommender setups • Must follow MLOps practices version control, CI/CD, monitoring, and infrastructure automation GCP Tools Experience: ML & AI : Vertex AI, Vertex Pipelines, Vertex AI Matching Engine, Kubeflow on GKE, AI Platform Embedding & Retrieval : Matching Engine, FAISS, ScaNN, Qdrant, GKE-hosted vector DBs (Milvus) Storage : BigQuery, Cloud Storage, Firestore Processing : Dataproc (PySpark), Dataflow (batch & stream) Ingestion : Pub/Sub, Cloud Functions, Cloud Run Serving : Vertex AI Online Prediction, TF Serving, Kubernetes-based custom APIs, Cloud Run CI/CD & IaC : GitHub Actions, GitLab CI

About this role: Wells Fargo is seeking a Lead Software Engineer within the Enterprise Application & Cloud Transformation team. In this role, you will: Lead complex technology Cloud initiatives including those that are companywide with broad impact. Act as a key contributor in automating the provisioning of Cloud Infrastructure using Infrastructure as a Code. Make decisions in developing standards and companywide best practices for engineering and large-scale technology solutions. Design, Optimization and Documentation of the Engineering aspects of the Cloud platform. Understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives. Review and analyze complex, large-scale technology solutions in Cloud for strategic business objectives and solving technical challenges that require in-depth evaluation of multiple parameters, including intangibles or unprecedented technical factors. Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals. Build and Enable cloud infrastructure, automate the orchestration of the entire GCP Cloud Platforms for Wells Fargo Enterprise. Working in a globally distributed team to provide innovative and robust Cloud centric solutions. Closely working with Product Team and Vendors to develop and deploy Cloud services to meet customer expectations. Required Qualifications: 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 3+ years working with GCP and a proven track record of building complex infrastructure programmatically with IaC tools. Must have 2+ years of hands-on experience with Infrastructure as Code tool Terraform and GitHub. Must have professional cloud certification on GCP. Proficient on container-based solution services, have handled at least 2-3 large scale Kubernetes based Infrastructure build out, provisioning of services GCP. Exposure to services like GKE, Cloud functions, Cloud Run, Cloud Build, Artifactory etc. Infrastructure and automation technologies: Orchestration, Harness, Terraform, Service Mesh, Kubernetes, API development, Test Driven Development Sound knowledge on the following areas with an expertise on one of them - 1. Proficient and have a thorough understanding of Cloud service offerings on Storage and Database. 2. Should have good understanding of networking, firewalls, load balancing concepts (IP, DNS, Guardrails, Vnets) and exposure to cloud security, AD, authentication methods, RBAC. 3. Proficient and have a thorough understanding of Cloud service offerings on Data, Analytics, AI/ML. Exposure to Analytics AIML services like BigQuery, Vertex AI, Data Proc etc. 4. Proficient and have a thorough understanding of Cloud service offerings on Security, Data Protection and Security policy implementations. Thorough understanding of landing zone and networking, Security best practices, Monitoring and logging, Risk and controls. Should have good understanding on Control Plane, Azure Arc and Google Anthos. Experience working in Agile environment and product backlog grooming against ongoing engineering work Enterprise Change Management and change control, experience working within procedural and process driven environment Desired Qualifications: Should have exposure to Cloud governance and logging/monitoring tools. Experience with Agile, CI/CD, DevOps concepts and SRE principles. Experience in scripting (Shell, Python, Go) Excellent verbal, written, and interpersonal communication skills. Ability to articulate technical solutions to both technical and business audiences Ability to deliver & engage with partners effectively in a multi-cultural environment by demonstrating co-ownership & accountability in a matrix structure. Delivery focus and willingness to work in a fast-paced, enterprise environment.

Job Description: AI Engineer (Junior / Associate Level) About the Role We are looking for a passionate and hands-on AI Developer with around 3 years of experience in building and deploying machine learning models and working with the latest AI tools and frameworks. You will be working closely with our data science and engineering teams to develop smart, scalable, and production-ready AI solutions. Key Responsibilities Design, develop, test, and deploy machine learning models for classification, regression, recommendation, or NLP tasks. Work with state-of-the-art AI tools and libraries such as LangChain, Hugging Face, OpenAI, LlamaIndex, etc. Integrate Large Language Models (LLMs) into applications via APIs or custom fine- tuning. Build data pipelines for training and inference, ensuring model performance and robustness. Collaborate with software developers, product managers, and data engineers to turn AI models into usable products. Stay updated with the latest research and innovations in the AI/ML space and bring new ideas into development. Optimize model performance and scale AI solutions for production. Required Skills & Experience Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. 2 to 4 years of hands-on experience in machine learning and deep learning. Proficiency in Python and libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy. Good understanding of LLMs and experience working with platforms like OpenAI, Claude, Cohere, or Hugging Face Transformers. Experience in prompt engineering, fine-tuning, or using frameworks like LangChain, LlamaIndex, or Haystack. Exposure to cloud platforms (AWS, GCP, Azure) and tools like Docker, Git, CI/CD workflows. Strong analytical and problem-solving skills. Understanding of data preprocessing, feature engineering, and model evaluation techniques. Good to Have Experience building AI chatbots or virtual assistants. Knowledge of Vector databases (e.g., Chroma, Pinecone, Weaviate). Familiarity with MLOps tools like MLflow, Kubeflow, Vertex AI, etc. Experience with RESTful APIs or microservices architecture. Participation in Kaggle competitions or open-source AI projects. What We Offer Opportunity to work on real-world AI applications and products. A collaborative, learning-first environment. Exposure to enterprise-grade AI deployments and tools. Flexible working hours and remote work options. Competitive compensation and career growth path.

Strong knowledge of Python, R, and ML frameworks such as scikit-learn, TensorFlow, PyTorch Experience with cloud ML platforms: SageMaker, Azure ML, Vertex AI LLM Experience such as GPT Hands-on experience with data wrangling, feature engineering, and model optimization Also experienced in developing model wrapers Deep understanding of algorithms including regression, classification, clustering, NLP, and deep learning Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow

Strong knowledge of Python, R, and ML frameworks such as scikit-learn, TensorFlow, PyTorch Experience with cloud ML platforms: SageMaker, Azure ML, Vertex AI LLM Experience such as GPT Hands-on experience with data wrangling, feature engineering, and model optimization Also experienced in developing model wrapers Deep understanding of algorithms including regression, classification, clustering, NLP, and deep learning Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow

Role & responsibilities We are seeking a skilled Data Engineer to join our team and enhance the efficiency and accuracy of health claim fraud detection. This role involves designing, building, and optimizing data pipelines, integrating AI/ML models in Vertex AI, and improving data processing workflows to detect fraudulent claims faster and more accurately. Qualifications: Bachelors/Masters degree in Computer Science, Data Engineering, or a related field. 3+ years of experience in data engineering, preferably in the healthcare or financial sector. Strong experience with Google Cloud (GCP) services: Vertex AI, BigQuery, Dataflow, Pub/Sub, Dataproc. Expertise in SQL and Python for data processing and transformation. Experience with ML model deployment and monitoring in Vertex AI. Knowledge of ETL pipelines, data governance, and security best practices. Familiarity with healthcare data standards (HL7, FHIR) and compliance frameworks. Experience with Apache Beam, Spark, or Kafka is a plus. Preferred Qualifications: Experience in fraud detection models using AI/ML. Hands-on experience with ML Ops in GCP. Strong problem-solving skills and the ability to work in a cross-functional team

Job Summary: UPS Enterprise Data Analytics team is looking for a talented and motivated Data Scientist to use statistical modelling, state of the art AI tools and techniques to solve complex and large-scale business problems for UPS operations. This role would also support debugging and enhancing existing AI applications in close collaboration with the Machine Learning Operations team. This position will work with multiple stakeholders across different levels of the organization to understand the business problem, develop and help implement robust and scalable solutions. You will be in a high visibility position with the opportunity to interact with the senior leadership to bring forth innovation within the operational space for UPS. Success in this role requires excellent communication to be able to present your cutting-edge solutions to both technical and business leaderships. Responsibilities: Become a subject matter expert on UPS business processes and data to help define and solve business needs using data, advanced statistical methods and AI Be actively involved in understanding and converting business use cases to technical requirements for modelling. Query, analyze and extract insights from large-scale structured and unstructured data from different data sources utilizing different platforms, methods and tools like BigQuery, Google Cloud Storage, etc. Understand and apply appropriate methods for cleaning and transforming data, engineering relevant features to be used for modelling. Actively drive modelling of business problem into ML/AI models, work closely with the stakeholders for model evaluation and acceptance. Work closely with the MLOps team to productionize new models, support enhancements and resolving any issues within existing production AI applications. Prepare extensive technical documentation, dashboards and presentations for technical and business stakeholders including leadership teams. Qualifications Expertise in Python, SQL. Experienced in using data science-based packages like scikit-learn, numpy, pandas, tensorflow, keras, statsmodels, etc. Strong understanding of statistical concepts and methods (like hypothesis testing, descriptive stats, etc.), machine learning techniques for regression, classification, clustering problems, including neural networks and deep learning. Proficient in using GCP tools like Vertex AI, BigQuery, GCS, etc. for model development and other activities in the ML lifecycle. Strong ownership and collaborative qualities in the relevant domain. Takes initiative to identify and drive opportunities for improvement and process streamline. Solid oral and written communication skills, especially around analytical concepts and methods. Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience. Masters Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications NLP, Gen AI, LLM knowledge/experience Knowledge of Operations Research methodologies and experience with packages like CPLEX, PULP, etc. Knowledge and experience in MLOps principles and tools in GCP. Experience working in an Agile environment, understanding of Lean Agile principles.

Site Reliability Engineers (SREs) - Robust background in Google Cloud Platform (GCP) | RedHat OpenShift administration Responsibilities: System Reliability: Ensure the reliability and uptime of critical services and infrastructure. Google Cloud Expertise: Design, implement, and manage cloud infrastructure using Google Cloud services. Automation: Develop and maintain automation scripts and tools to improve system efficiency and reduce manual intervention. Monitoring and Incident Response: Implement monitoring solutions and respond to incidents to minimize downtime and ensure quick recovery. Collaboration: Work closely with development and operations teams to improve system reliability and performance. Capacity Planning: Conduct capacity planning and performance tuning to ensure systems can handle future growth. Documentation: Create and maintain comprehensive documentation for system configurations, processes, and procedures. Qualifications: Education: Bachelors degree in computer science, Engineering, or a related field. Experience: 4+ years of experience in site reliability engineering or a similar role. Skills: Proficiency in Google Cloud services (Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery, Pub/Sub, etc.). Familiarity with Google BI and AI/ML tools (Looker, BigQuery ML, Vertex AI, etc.) Experience with automation tools (Terraform, Ansible, Puppet). Familiarity with CI/CD pipelines and tools (Azure pipelines Jenkins, GitLab CI, etc.). Strong scripting skills (Python, Bash, etc.). Knowledge of networking concepts and protocols. Experience with monitoring tools (Prometheus, Grafana, etc.). Preferred Certifications: Google Cloud Professional DevOps Engineer Google Cloud Professional Cloud Architect Red Hat Certified Engineer (RHCE) or similar Linux certification

Strong knowledge of Python, R, and ML frameworks such as scikit-learn, TensorFlow, PyTorch. Experience with cloud ML platforms: SageMaker, Azure ML, Vertex AI.LLM Experience such as GPT Hands-on experience with data wrangling, feature engineering, and model optimization. Also experienced in developing model wrapers. Deep understanding of algorithms including regression, classification, clustering, NLP, and deep learning. Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow.

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the worlds leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Job Description As an LLM (Large Language Model) Engineer, you will be responsible for designing, optimizing, and standardizing the architecture, codebase, and deployment pipelines of LLM-based systems. Your primary mission will focus on modernizing legacy machine learning codebases (including 40+ models) for a major retail clientenabling consistency, modularity, observability, and readiness for GenAI-driven innovation. You’ll work at the intersection of ML, software engineering, and MLOps to enable seamless experimentation, robust infrastructure, and production-grade performance for language-driven systems. This role requires deep expertise in NLP, transformer-based models, and the evolving ecosystem of LLM operations (LLMOps), along with a hands-on approach to debugging, refactoring, and building unified frameworks for scalable GenAI workloads. Responsibilities: Lead the standardization and modernization of legacy ML codebases by aligning to current LLM architecture best practices. Re-architect code for 40+ legacy ML models, ensuring modularity, documentation, and consistent design patterns. Design and maintain pipelines for fine-tuning, evaluation, and inference of LLMs using Hugging Face, OpenAI, or opensource stacks (e.g., LLaMA, Mistral, Falcon). Build frameworks to operationalize prompt engineering, retrieval-augmented generation (RAG), and few-shot/incontext learning methods. Collaborate with Data Scientists, MLOps Engineers, and Platform teams to implement scalable CI/CD pipelines, feature stores, model registries, and unified experiment tracking. Benchmark model performance, latency, and cost across multiple deployment environments (on-premise, GCP, Azure). Develop governance, access control, and audit logging mechanisms for LLM outputs to ensure data safety and compliance. Mentor engineering teams in code best practices, versioning, and LLM lifecycle maintenance. Key Skills: Deep understanding of transformer architectures, tokenization, attention mechanisms, and training/inference optimization Proven track record in standardizing ML systems using OOP design, reusable components, and scalable service APIs Hands-on experience with MLflow, LangChain, Ray, Prefect/Airflow, Docker, K8s, Weights & Biases, and modelserving platforms. Strong grasp of prompt tuning, evaluation metrics, context window management, and hybrid search strategies using vector databases like FAISS, pgvector, or Milvus Proficient in Python (must), with working knowledge of shell scripting, YAML, and JSON schema standardization Experience managing compute, memory, and storage requirements of LLMs across GCP, Azure, or AWS environments Qualifications & Experience: 5+ years in ML/AI engineering with at least 2 years working on LLMs or NLP-heavy systems. Able to reverse-engineer undocumented code and reimagine it with strong documentation and testing in mind. Clear communicator who collaborates well with business, data science, and DevOps teams. Familiar with agile processes, JIRA, GitOps, and confluence-based knowledge sharing. Curious and future-facing—always exploring new techniques and pushing the envelope on GenAI innovation. Passionate about data ethics, responsible AI, and building inclusive systems that scale

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 - GCP AI Engineer! In this role, We are seeking an experienced and passionate GCP AI Engineer to join our team and drive innovation through the application of artificial intelligence solutions on the Google Cloud Platform (GCP). The ideal candidate will have a strong understanding of AI principles, cloud computing, and a track record of delivering impactful AI-driven projects. Responsibilities 1. GCP AI Solutions Development: Design and develop AI solutions using GCP AI services, including Vertex AI, BigQuery ML, and other specialized AI tools. 2. Data Preprocessing and Engineering: Preprocess and engineer large datasets using GCP data tools and techniques to prepare them for AI model training. 3. Model Training and Deployment: Train and deploy AI models on GCP, optimizing model performance and efficiency while ensuring scalability and reliability. 4. Algorithm Selection and Tuning: Select appropriate AI algorithms and hyperparameters for specific business problems, and tune models to achieve optimal performance. 5. Cloud Infrastructure Management: Provision and manage GCP cloud infrastructure, including virtual machines, containers, and storage systems, to support AI workloads. 6. Performance Monitoring and Optimization: Continuously monitor and evaluate AI models in production, identifying and addressing performance bottlenecks and opportunities for optimization. 7. Collaboration and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deliver end-to-end AI solutions. 8. Documentation and Knowledge Sharing: Document AI project methodologies, findings, and best practices, and share knowledge with the broader team to foster a culture of innovation. 9. Stay Up-to-Date : Keep abreast of the latest advancements in AI and GCP AI services, attending conferences, workshops, and training programs to enhance skills and knowledge. 10. Hands on experience developing solutions with GCP%27s ML APIs. Qualifications we seek in you! Minimum Qualification s . Bachelor&rsquos degree or equivalent experience in Computer Science, Artificial Intelligence, or a related field. . Relevant experience in AI development and deployment, with a focus on GCP AI services. . Strong programming skills in Python and proficiency with cloud-based AI frameworks and libraries. . Solid understanding of machine learning algorithms, including supervised and unsupervised learning, and deep learning architectures. . Experience with natural language processing, computer vision, or other specialized AI domains is a plus. . Familiarity with GCP data management tools and services, such as BigQuery , Cloud Storage, and Cloud Dataflow. Preferred Qualifications/ Skills . Excellent problem-solving skills and a strong analytical mindset. . Strong communication skills, both written and verbal, with the ability to explain technical concepts to non-technical stakeholders. . Ability to work independently and as part of a team in a fast-paced, dynamic environment. . Passion for AI and its potential to solve real-world problems using GCP technologies. 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.

We are hiring Senior Machine Learning Engineer for an MNC Job Type : Direct , Fulltime role Location : PAN India (Remote) Senior Machine Learning Engineer Responsibilities Develop, implement, and maintain machine learning models using scikit-learn and SciPy. Build and deploy ML models for production use cases. Work with regression models and optimization techniques. Develop and integrate APIs using the Flask framework. Utilize GCP services (App Engine, Cloud Tasks, Dataflow, BigQuery, Bigtable, Vertex AI). Optimize CI/CD pipelines using Azure DevOps. Collaborate with cross-functional teams to deploy scalable ML solutions. Qualifications Strong proficiency in Python and core ML libraries Scikit-learn and SciPy. Hands-on experience with regression models and optimization techniques. Experience with Flask for API development and deployment. Proficiency in GCP services and ML operations on cloud infrastructure. Experience with CI/CD tools, especially Azure DevOps. Solid understanding of data structures, algorithms, and software engineering practices. Familiarity with Agile methodologies and technical documentation. Strong analytical, communication, and problem-solving skills.

Key Responsibilities Design and implement GenAI architectures leveraging Google Cloud and Gemini AI models Lead solution architecture and integration of generative AI models into enterprise applications Collaborate with data scientists engineers and business stakeholders to define AI use cases and technical strategy Develop and optimize prompt engineering, model fine tuning, and deployment pipelines Design scalable data storage and retrieval layers using PostgreSQL BigQuery and vector databases e.g.Vertex AI Search Pinecone or FAISS Evaluate third party GenAI APIs and tools for integration Ensure compliance with data security privacy and responsible AI guidelines Support performance tuning monitoring and optimization of AI solutions in production Stay updated with evolving trends in GenAI and GCP offerings especially related to Gemini and Vertex AI Required Skills and Qualifications Proven experience architecting AI and ML or GenAI systems on Google Cloud Platform Hands-on experience with Google Gemini Vertex AI and related GCP AI tools Strong understanding of LLMs, prompt engineering and text generation frameworks Proficiency in PostgreSQL, including advanced SQL and performance tuning Experience with MLOps, CI and CD pipelines, and AI model lifecycle management Solid knowledge of Python, APIs, RESTful services, and cloud native architecture Familiarity with vector databases and semantic search concepts Strong communication and stakeholder management skills Preferred Qualifications GCP certifications e.g., Professional Cloud Architect Machine Learning Engineer Experience in model fine-tuning and custom LLM training Knowledge of LangChain, RAG Retrieval Augmented Generation frameworks Exposure to data privacy regulations GDPR, HIPAA, etc. Background in natural language processing NLP and deep learning

Role - Machine Learning Engineer Required Skills & Experience 5+ years of hands-on experience in building, training, and deploying machine learning models in a professional, production-oriented setting. Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts. Proven expertise in data blending, transformation, and feature engineering , adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data. Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable. Proficiency in programming languages commonly used in data science (e.g., Python is preferred, R). Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like Deep Learning, Natural Language Processing (NLP), or Computer Vision . Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ). Familiarity with MLOps tools and practices , including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines. Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs. Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development. Interested candidates share cv to dikshith.nalapatla@motivitylabs.com

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.