91 Vertex Ai Jobs

You are a highly skilled and motivated Technical Lead who will be joining our growing team. Your role will involve leading and delivering complex technical projects in areas such as AI/ML, Full Stack Development, and Cloud-based solutions. Your responsibilities will include overseeing the end-to-end execution of multiple software development projects, focusing on AI/ML initiatives and products to ensure timely delivery and high quality. You will be responsible for architecture design, technical planning, and code quality across the team, specifically for scalable AI/ML solutions, robust data pipelines, and integration of models into production systems. Collaboration with stakeholders, both internal and external, will be a key part of your role. You will gather requirements for AI/ML features, provide progress updates, and effectively manage expectations. Mentoring and guiding developers to foster a culture of continuous improvement and technical excellence, especially in AI/ML best practices, model development, and ethical AI considerations, will be essential. You will work closely with cross-functional teams, including QA, DevOps, and UI/UX designers, to seamlessly integrate AI/ML models and applications into broader systems. Implementing best practices in development, deployment, and version control with a strong emphasis on MLOps and reproducible AI/ML workflows is crucial. Tracking project milestones, managing technical risks, and ensuring that AI/ML projects align with overarching business goals will be part of your responsibilities. Participating in client calls to provide technical insights and solution presentations, demonstrating the value and capabilities of our AI/ML offerings, will be required. Driving research, experimentation, and adoption of cutting-edge AI/ML algorithms and techniques to enhance product capabilities is also expected from you. Required Skills: - Strong hands-on experience in at least one Fullstack framework (e.g., MERN stack, Python with React). - Proven experience managing and delivering end-to-end AI/ML projects or products. - Proficiency in major AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn. - Solid experience with data processing, feature engineering, and data pipeline construction for machine learning workloads. - Proficiency in project tracking tools like Jira, Trello, or Asana. - Solid understanding of SDLC, Agile methodologies, and CI/CD practices. - Strong knowledge of cloud platforms like AWS, Azure, or GCP, especially their AI/ML services. - Excellent problem-solving, communication, and leadership skills. Preferred Qualifications: - Bachelor's or Master's degree in a related field. - Experience with containerization technologies and microservices architecture. - Exposure to MLOps practices and tools. - Prior experience in a client-facing technical leadership role. - Familiarity with big data technologies. - Contributions to open-source AI/ML projects or relevant publications are a plus. (ref:hirist.tech),

Role: Capability Lead GCP Location: Bengaluru / Hyderabad / Chennai Job Summary We are seeking a dynamic and visionary Capability Lead GCP to lead and scale our Google Cloud Platform practice. This is a senior leadership role that involves working directly with vertical business leaders to shape and deliver data-driven cloud strategies. The ideal candidate will bring a strong blend of technical depth, strategic thinking, and the ability to provide solutions that align with organizational goals. This role is critical to driving digital transformation across the enterprise and will act as a key advisor to senior stakeholders. Key Responsibilities Act as a strategic partner to vertical and business unit leaders, helping shape their cloud data strategy and providing tailored GCP-based solutions to solve business challenges. Own and lead the Data & Analytics capability on GCP, including strategy, delivery governance, presales, and innovation. Design and implement cloud-native data architectures using GCP services such as BigQuery, Looker, Dataflow, Pub/Sub, and Vertex AI. Lead client engagements end-to-end, including stakeholder workshops, solution design, proposals, estimations, and proof of concepts (POCs). Collaborate with internal business teams and Google Cloud to define go-to-market strategies and reusable solution accelerators. Guide organisations through cloud transformation journeys with an emphasis on data modernisation, governance, and scalable analytics platforms. Build, lead, and mentor a team of engineers, architects, and consultants, promoting continuous learning and GCP certifications. Stay ahead of emerging GCP trends and influence internal and external stakeholders on adoption strategies. Show more Show less

As a Senior Machine Learning Engineer with over 10 years of experience, you will play a crucial role in designing, building, and deploying scalable machine learning systems in production. In this role, you will collaborate closely with data scientists to operationalize models, take ownership of ML pipelines from end to end, and enhance the reliability, automation, and performance of our ML infrastructure. Your primary responsibilities will include designing and constructing robust ML pipelines and services for training, validation, and model deployment. You will work in collaboration with various stakeholders such as data scientists, solution architects, and DevOps engineers to ensure alignment with project goals and requirements. Additionally, you will be responsible for ensuring cloud integration compatibility with AWS and Azure, building reusable infrastructure components following best practices in DevOps and MLOps, and adhering to security standards and regulatory compliance. To excel in this role, you should possess strong programming skills in Python, have deep experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, and be proficient in MLOps tools like MLflow, Airflow, TFX, Kubeflow, or BentoML. Experience in deploying models using Docker and Kubernetes, familiarity with cloud platforms and ML services, and proficiency in data engineering tools are essential for success in this position. Additionally, knowledge of CI/CD, version control, and infrastructure as code along with experience in monitoring/logging tools will be advantageous. Good-to-have skills include experience with feature stores and experiment tracking platforms, knowledge of edge/embedded ML, model quantization, and optimization, as well as familiarity with model governance, security, and compliance in ML systems. Exposure to on-device ML or streaming ML use cases and experience in leading cross-functional initiatives or mentoring junior engineers will also be beneficial. Joining Ericsson will provide you with an exceptional opportunity to leverage your skills and creativity to address some of the world's toughest challenges. You will be part of a diverse team of innovators who are committed to pushing the boundaries of innovation and crafting groundbreaking solutions. As a member of this team, you will be challenged to think beyond conventional limits and contribute to shaping the future of technology.,

You will be responsible for solution design, client engagement, and delivery oversight, along with senior stakeholder management. Your role will involve leading and driving Google Cloud solutioning for customer requirements, RFPs, proposals, and delivery. You will establish governance frameworks, delivery methodologies, and reusable assets to scale the practice. It is essential to have the ability to take initiative and deliver in challenging engagements spread across multiple geographies. Additionally, you will lead the development of differentiated capabilities and offerings in areas such as application modernization & migration, cloud-native development, and AI agents. Collaboration with sales and pre-sales teams to shape solutions and win strategic deals, including large-scale application modernization and migrations will be a key aspect of your role. You will spearhead Google Cloud's latest products & services like AgentSpace, AI Agent development using GCP-native tools such as ADK, A2A Protocol, and Model Context Protocol. Building and mentoring a high-performing team of cloud architects, engineers, and consultants will also be part of your responsibilities. Driving internal certifications, specialization audits, and partner assessments to maintain Google Cloud Partner status is crucial. Representing the organization in partner forums, webinars, and industry/customer events is also expected from you. To qualify for this role, you should have 15+ years of experience in IT, with at least 3 years in Google Cloud applications architecture, design, and solutioning. Additionally, a minimum of 5 years of experience in designing and developing Java applications/platforms is required. Deep expertise in GCP services including Compute, Storage, BigQuery, Cloud Functions, Anthos, and Vertex AI is essential. Proven experience in leading Google Cloud transformation programs, strong solution architecture, and implementation experience for Google Cloud modernization & migration programs are important qualifications. Strong experience in stakeholder and client management is also necessary. Being Google Cloud certified with the Google Cloud Professional architect certification, self-motivated to quickly learn new technologies and platforms, and possessing excellent presentation and communication skills are crucial for this role. Preferred qualifications include Google Cloud Professional certifications (Cloud Architect), experience with partner ecosystems, co-selling with Google, and managing joint GTM motions, as well as exposure to regulated industries (e.g., BFSI, Healthcare) and global delivery models.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

You will be working as an AI Platform Engineer in Bangalore as part of the GenAI COE Team. Your key responsibilities will involve developing and promoting scalable AI platforms for customer-facing applications. It will be essential to evangelize the platform with customers and internal stakeholders, ensuring scalability, reliability, and performance to meet business needs. Your role will also entail designing machine learning pipelines for experiment management, model management, feature management, and model retraining. Implementing A/B testing of models and designing APIs for model inferencing at scale will be crucial. You should have proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. As an AI Platform Engineer, you will serve as a subject matter expert in LLM serving paradigms, with in-depth knowledge of GPU architectures. Expertise in distributed training and serving of large language models, along with proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM, will be required. Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results will be part of your responsibilities. Reducing training and resource requirements for fine-tuning LLM and LVM models will also be essential. Having extensive knowledge of different LLM models and providing insights on their applicability based on use cases is crucial. You should have proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. Your proficiency in DevOps and LLMOps practices, along with knowledge of Kubernetes, Docker, and container orchestration, will be necessary. A deep understanding of LLM orchestration frameworks such as Flowise, Langflow, and Langgraph is also required. In terms of skills, you should be familiar with LLM models like Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, and Llama, as well as LLM Ops tools like ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, and Azure AI. Additionally, knowledge of databases/data warehouse systems like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, and Google BigQuery, as well as cloud platforms such as AWS, Azure, and GCP, is essential. Proficiency in DevOps tools like Kubernetes, Docker, FluentD, Kibana, Grafana, and Prometheus, along with cloud certifications like AWS Professional Solution Architect and Azure Solutions Architect Expert, will be beneficial. Strong programming skills in Python, SQL, and Javascript are required for this full-time role, with an in-person work location.,

Sabre is a technology company that powers the global travel industry. By leveraging next-generation technology, we create global technology solutions that take on the biggest opportunities and solve the most complex challenges in travel. Positioned at the center of the travel industry, we shape the future by offering innovative advancements that pave the way for a more connected and seamless ecosystem. Our solutions power mobile apps, online travel sites, airline and hotel reservation networks, travel agent terminals, and many other platforms, connecting people with moments that matter. Sabre is seeking a talented senior software engineer full Senior Data Science Engineer for SabreMosaic Team. In this role, you will plan, design, develop, and test data science and data engineering software systems or applications for software enhancements and new products based on cloud-based solutions. Role and Responsibilities: - Develop, code, test, and debug new complex data-driven software solutions or enhancements to existing products. - Design, plan, develop, and improve applications using advanced cloud-native technology. - Work on issues requiring in-depth knowledge of organizational objectives and implement strategic policies in selecting methods and techniques. - Encourage high coding standards, best practices, and high-quality output. - Interact regularly with subordinate supervisors, architects, product managers, HR, and others on project or team performance matters. - Provide technical mentorship and cultural/competency-based guidance to teams. - Offer larger business/product context and mentor on specific tech stacks/technologies. Qualifications and Education Requirements: - Minimum 4-6 years of related experience as a full-stack developer. - Expertise in Data Engineering/DW projects with Google Cloud-based solutions. - Designing and developing enterprise data solutions on the GCP cloud platform. - Experience with relational databases and NoSQL databases like Oracle, Spanner, BigQuery, etc. - Expert-level SQL skills for data manipulation, validation, and manipulation. - Experience in designing data modeling, data warehouses, data lakes, and analytics platforms on GCP. - Expertise in designing ETL data pipelines and data processing architectures for Datawarehouse. - Strong experience in designing Star & Snowflake Schemas and knowledge of Dimensional Data Modeling. - Collaboration with data scientists, data teams, and engineering teams using Google Cloud platform for data analysis and data modeling. - Familiarity with integrating datasets from multiple sources for data modeling for analytical and AI/ML models. - Understanding and experience in Pub/Sub, Kafka, Kubernetes, GCP, AWS, Hive, Docker. - Expertise in Java Spring Boot / Python or other programming languages used for Data Engineering and integration projects. - Strong problem-solving and analytical skills. - Exposure to AI/ML, MLOPS, and Vertex AI is an advantage. - Familiarity with DevOps practices like CICD pipeline. - Airline domain experience is a plus. - Excellent spoken and written communication skills. - GCP Cloud Data Engineer Professional certification is a plus. We will carefully consider your application and review your details against the position criteria. Only candidates who meet the minimum criteria for the role will proceed in the selection process.,

Job Title: Data Science Expert (Mentor & Trainer) Location: Onsite Mumbai, India Employment Type: Full-Time About the Role: We are seeking an experienced and highly skilled Data Science Expert to join our growing team at our Mumbai office. This is a full-time, onsite role focused not only on solving complex data problems but also on mentoring and training Junior Data Science Engineers . The ideal candidate will bring deep technical expertise in data science and machine learning, along with a passion for teaching and developing talent. Key Responsibilities: Lead the development of end-to-end data science solutions using advanced ML, NLP, and Computer Vision techniques. Train, mentor, and support junior data science engineers in coding, model development, and best practices. Architect and implement AI-driven solutions such as chatbots, OCR systems, and facial recognition applications. Translate complex business problems into actionable data science projects and deliver measurable results. Design and lead internal workshops, code reviews, and learning sessions to upskill the team. Collaborate with engineering and product teams to deploy models and insights into production environments. Stay abreast of the latest AI/ML trends and integrate cutting-edge techniques into projects where applicable. Desired Skills & Qualifications: Experience: 6+ years in Data Science/Machine Learning with at least 12 years of team mentoring or leadership experience. Education: Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. Technical Expertise Required: Strong proficiency in Python and SQL ; R is a plus. Solid hands-on experience with Deep Learning and Neural Networks , particularly in Natural Language Processing (NLP) , Generative AI , and Computer Vision . Familiarity with frameworks and libraries such as TensorFlow , Keras , PyTorch , OpenCV , SpaCy , NLTK , BERT , ELMo , etc. Experience developing Chatbots , OCR , and Face Recognition systems is preferred. Hands-on knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform). Experience applying statistical and data mining techniques such as GLM , regression , clustering , random forests , boosting , decision trees , etc. Strong understanding of model validation , performance tuning , and deployment strategies . Soft Skills: Excellent communication and presentation skills, especially in explaining complex models to non-technical audiences. Demonstrated ability to mentor, train, and lead junior team members effectively. Strong analytical and problem-solving mindset with a detail-oriented approach. What We Offer: Competitive salary and benefits A collaborative and intellectually stimulating environment Career growth and leadership development opportunities within a fast-paced team

Overview of 66degrees 66degrees is a leading consulting and professional services company specializing in developing AI-focused, data-led solutions leveraging the latest advancements in cloud technology. With our unmatched engineering capabilities and vast industry experience, we help the world&aposs leading brands transform their business challenges into opportunities and shape the future of work. At 66degrees, we believe in embracing the challenge and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way. Overview of Role As a Data Engineer specializing in AI/ML, you&aposll be instrumental in designing, building, and maintaining the data infrastructure crucial for training, deploying, and serving our advanced AI and Machine Learning models. You&aposll work closely with Data Scientists, ML Engineers, and Cloud Architects to ensure data is accessible, reliable, and optimized for high-performance AI/ML workloads, primarily within the Google Cloud ecosystem. Responsibilities Data Pipeline Development: Design, build, and maintain robust, scalable, and efficient ETL/ELT data pipelines to ingest, transform, and load data from various sources into data lakes and data warehouses, specifically optimized for AI/ML consumption. AI/ML Data Infrastructure: Architect and implement the underlying data infrastructure required for machine learning model training, serving, and monitoring within GCP environments. Google Cloud Ecosystem: Leverage a broad range of Google Cloud Platform (GCP) data services including, BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Vertex AI, Composer (Airflow), and Cloud SQL. Data Quality & Governance: Implement best practices for data quality, data governance, data lineage, and data security to ensure the reliability and integrity of AI/ML datasets. Performance Optimization: Optimize data pipelines and storage solutions for performance, cost-efficiency, and scalability, particularly for large-scale AI/ML data processing. Collaboration with AI/ML Teams: Work closely with Data Scientists and ML Engineers to understand their data needs, prepare datasets for model training, and assist in deploying models into production. Automation & MLOps Support: Contribute to the automation of data pipelines and support MLOps initiatives, ensuring seamless integration from data ingestion to model deployment and monitoring. Troubleshooting & Support: Troubleshoot and resolve data-related issues within the AI/ML ecosystem, ensuring data availability and pipeline health. Documentation: Create and maintain comprehensive documentation for data architectures, pipelines, and data models. Qualifications 1-2+ years of experience in Data Engineering, with at least 2-3 years directly focused on building data pipelines for AI/ML workloads. Deep, hands-on experience with core GCP data services such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Composer/Airflow. Strong proficiency in at least one relevant programming language for data engineering (Python is highly preferred).SQL skills for complex data manipulation, querying, and optimization. Solid understanding of data warehousing concepts, data modeling (dimensional, 3NF), and schema design for analytical and AI/ML purposes. Proven experience designing, building, and optimizing large-scale ETL/ELT processes. Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and concepts. Exceptional analytical and problem-solving skills, with the ability to design solutions for complex data challenges. Excellent verbal and written communication skills, capable of explaining complex technical concepts to both technical and non-technical stakeholders. 66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class. Show more Show less

Before you apply to a job, select your language preference from the options available at the top right of this page. Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrowpeople with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level. Job Description Google Cloud Infrastructure Support Engineer will be responsible for ensuring the reliability, performance, and security of our Google Cloud Platform (GCP) infrastructure. Work closely with cross-functional teams to troubleshoot issues, optimize infrastructure, and implement best practices for cloud architecture. Experience with Terraform for deploying and managing infrastructure templates. Administer BigQuery environments, including managing datasets, access controls, and optimize query performance. Be familiar with Vertex AI for monitoring and managing machine learning model deployments. Knowledge of GCPs Kubernetes Engine and its integration with the cloud ecosystem. Understanding of cloud security best practices and experience with implementing security measures. Knowledge of setting up and managing data clean rooms within BigQuery. Understanding of the Analytics Hub platform and how it integrates with data clean rooms to facilitate sensitive data-sharing use cases. Knowledge of DataPlex and how it integrates with other Google Cloud services such as BigQuery, Dataproc Metastore, and Data Catalog. Key Responsibilities Provide technical support for our Google Cloud Platform infrastructure, including compute, storage, networking, and security services. Monitor system performance and proactively identify and resolve issues to ensure maximum uptime and reliability. Collaborate with cross-functional teams to design, implement, and optimize cloud infrastructure solutions. Automate repetitive tasks and develop scripts to streamline operations and improve efficiency. Document infrastructure configurations, processes, and procedures. Qualifications Required: Strong understanding of GCP services, including Compute Engine, Kubernetes Engine, Cloud Storage, VPC networking, and IAM. Experience with BigQuery and VertexAI Proficiency in scripting languages such as Python, Bash, or PowerShell. Experience with infrastructure as code tools such as Terraform or Google Deployment Manager. Strong communication and collaboration skills. Bachelor&aposs Degree in Computer Science or related discipline, or the equivalent in education and work experience Preferred Google Cloud certification (e.g., Google Cloud Certified - Professional Cloud Architect, Google Cloud Certified - Professional Cloud DevOps Engineer) Employee Type Permanent UPS is committed to providing a workplace free of discrimination, harassment, and retaliation. Show more Show less

About this role: Wells Fargo is seeking a Principal Engineer. We believe in the power of working together because great ideas can come from anyone. Through collaboration, any employee can have an impact and make a difference for the entire company. Explore opportunities with us for a career in a supportive environment where you can learn and grow. In this role, you will: Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: 5+ years of experience in Cloud Native Application 5+ years of User Interface (UI) experience such as, Angular or React 5+ years of event driven development, microservice architecture, API designs 5+ years of experience using development toolkit including Jenkins, GitHub, and Bitbucket 3+ years working with public cloud platforms (i.e. Google Cloud/Vertex AI, AWS and Azure) and hands on experience with Prompt Engineering, AI/ML frameworks (i.e. TensorFlow, Pytorch) Knowledge and understanding of relational and non-relational databases, such as PostgreSQL, SQL Server, MongoDB, Neo4J etc Role: Head - Engineering Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: Any Graduate PG: Any Postgraduate

You are a highly skilled and motivated Lead Data Scientist / Machine Learning Engineer sought to join a team pivotal in the development of a cutting-edge reporting platform. This platform is designed to measure and optimize online marketing campaigns effectively. Your role will involve focusing on data engineering, ML model lifecycle, and cloud-native technologies. You will be responsible for designing, building, and maintaining scalable ELT pipelines, ensuring high data quality, integrity, and governance. Additionally, you will develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experimenting with different algorithms and leveraging various models will be crucial in driving insights and recommendations. Furthermore, you will deploy and monitor ML models in production and implement CI/CD pipelines for seamless updates and retraining. You will work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translating complex model insights into actionable business recommendations and presenting findings to stakeholders will also be part of your responsibilities. Qualifications & Skills: Educational Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or related field. - Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: - Experience: 5-10 years with the mentioned skillset & relevant hands-on experience. - Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). - ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: - Experience with Graph ML, reinforcement learning, or causal inference modeling. - Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray). Location: - Bengaluru Brand: - Merkle Time Type: - Full time Contract Type: - Permanent,

About KPMG in India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. We are seeking an experienced and highly skilled Senior Google Cloud Analytics & Vertex AI Specialist for the position of Associate Director with 12-15 years of experience, specifically focusing on Google Vertex AI. The ideal candidate will have a deep understanding of Google Cloud Platform (GCP) and extensive hands-on experience with Google Cloud analytics services and Vertex AI. The role involves leading projects, designing scalable data solutions, driving the adoption of AI and machine learning practices within the organization, and supporting pre-sales activities. A minimum of 2 years of hands-on experience with Vertex AI is required. Key Responsibilities: - Architect and Implement: Design and implement end-to-end data analytics solutions using Google Cloud services such as BigQuery, Dataflow, Pub/Sub, and Cloud Storage. - Vertex AI Development: Develop, train, and deploy machine learning models using Vertex AI. Utilize Vertex AI's integrated tools for model monitoring, versioning, and CI/CD pipelines. Implement custom machine learning pipelines using Vertex AI Pipelines. Utilize Vertex AI Feature Store for feature management and Vertex AI Model Registry for model tracking. - Data Integration: Integrate data from various sources, ensuring data quality and consistency across different systems. - Performance Optimization: Optimize data pipelines and analytics processes for maximum efficiency and performance. - Leadership and Mentorship: Lead and mentor a team of data engineers and data scientists, providing guidance and support on best practices in GCP and AI/ML. - Collaboration: Work closely with stakeholders to understand business requirements and translate them into technical solutions. - Innovation: Stay updated with the latest trends and advancements in Google Cloud services and AI technologies, advocating for their adoption when beneficial. - Pre-Sales Support: Collaborate cross-functionally to understand client requirements, design tailored solutions, prepare and deliver technical presentations and product demonstrations, and assist in proposal and RFP responses. - Project Delivery: Manage and oversee the delivery of data analytics and AI/ML projects, ensuring timely and within budget completion while coordinating with cross-functional teams. Qualifications: - Experience: 12-15 years in data engineering, data analytics, and AI/ML with a focus on Google Cloud Platform. - Technical Skills: Proficient in Google Cloud services (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Vertex AI), strong programming skills in Python and SQL, experience with machine learning frameworks (TensorFlow, PyTorch), data visualization tools (Looker, Data Studio). - Pre-Sales and Delivery Skills: Experience in supporting pre-sales activities, managing and delivering complex data analytics and AI/ML projects. - Certifications: Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification is a plus. - Soft Skills: Excellent problem-solving, communication, and leadership skills. Qualifications: - B.E./B.Tech/Post Graduate,

We are seeking a talented Systems Architect (AVP level) with specialized knowledge in designing and expanding Generative AI solutions for production environments. In this pivotal position, you will collaborate across various teams including data scientists, ML engineers, and product leaders to mold enterprise-level GenAI platforms. Your responsibilities will include designing and scaling LLM-based systems such as chatbots, copilots, RAG, and multi-modal AI, architecting data pipelines, training/inference workflows, and integrating MLOps. You will be tasked with ensuring that systems are modular, secure, scalable, and cost-effective. Additionally, you will work on model orchestration, agentic AI, vector DBs, and CI/CD for AI. The ideal candidate should possess 12-15 years of experience in cloud-native and distributed systems, with 2-3 years focusing on GenAI/LLMs utilizing tools like LangChain, HuggingFace, and Kubeflow. Proficiency in cloud platforms such as AWS, GCP, or Azure (SageMaker, Vertex AI, Azure ML) is essential. Experience with RAG, semantic search, agent orchestration, and MLOps is highly valued. Strong architectural acumen, effective stakeholder communication skills, and preferred certifications in cloud technologies, AI open-source contributions, and knowledge of security and governance are all advantageous.,

We are looking for a Systems Architect (AVP level) with extensive experience in designing and scaling Generative AI solutions for production. As a Systems Architect, you will play a crucial role in collaborating with data scientists, ML engineers, and product leaders to shape enterprise-grade GenAI platforms. Your responsibilities will include designing and scaling LLM-based systems such as chatbots, copilots, RAG, and multi-modal AI. You will also be responsible for architecting data pipelines, training/inference workflows, and MLOps integration. It is essential to ensure that the systems you design are modular, secure, scalable, and cost-effective. Additionally, you will work on model orchestration, agentic AI, vector DBs, and CI/CD for AI. The ideal candidate should have 12-15 years of experience in cloud-native and distributed systems, with at least 2-3 years of experience in GenAI/LLMs using tools like LangChain, HuggingFace, and Kubeflow. Proficiency in cloud platforms such as AWS, GCP, or Azure (SageMaker, Vertex AI, Azure ML) is required. Experience with technologies like RAG, semantic search, agent orchestration, and MLOps will be beneficial for this role. Strong architectural thinking and effective communication with stakeholders are essential skills. Preferred qualifications include cloud certifications, AI open-source contributions, and knowledge of security and governance principles. If you are passionate about designing cutting-edge Generative AI solutions and possess the necessary skills and experience, we encourage you to apply for this leadership role.,

Role & responsibilities 1.Develop and execute a strategic roadmap for executing Applied AI engineering projects with a product engineering mindset . 2. Lead and inspire a high-performance core group of developers, architects & engineering managers. 3. Responsible for hiring, training, coaching, team building, assessing performance, providing feedback, mentoring, and helping the team succeed. Our enthusiastic Data Scientists are just getting started -- and as a manager, you guide the way and set up examples by coming up with the best solutions to complex engineering problems. 4. Collaborate with architects, product management, and other engineering teams to create solutions that increase the platform's value. 5. Own Delivery - This includes overseeing the end-to-end delivery of Applied AI projects, ensuring adherence to timelines, budget, and impeccable engineering quality, setting up and managing periodic progress meeting,s and act as a point of escalation for project issues, providing timely resolution and effective communication with stakeholders. 6. Participate with senior management in developing a long-term technology road map. Influence, collaborate and communicate effectively with various leaders. Education and Qualification 1.Proven experience of 10+ years in a leadership role overseeing Applied AI engineering teams, preferably within a professional services environment. 2. Successful track-record of Solution Architecting and High-end AI based software development. 3. Strong technical background with expertise in Generative AI, Google AI APIs, Machine Learning, software development methodologies, languages, and frameworks. 4. Excellent communication skills with the ability to articulate technical concepts to both technical and non-technical audiences. 5. Demonstrated success in delivering complex software projects on time and within budget. 6. Ability to thrive in a fast-paced, dynamic environment and adapt to evolving business needs. 7. Leadership qualities including strategic thinking, decision-making, problem-solving, and team-building. 8. Experience in client-facing roles with a focus on building and maintaining relationships. 9. Our technology stack is insane and the role requires experience and understanding of technologies like: a. Python, Pyspark , TensorFlow b. Databases: MongoDB, Google Cloud SQL, Graph/NoSQL, Bigtable c. Google App Engine, GKE, Vertex A I , Doc AI, Conversational AI

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

You will be joining our team as a Machine Learning / AI expert with 4-7 years of experience, dedicated to creating impactful GenAI solutions using Vertex AI on Google Cloud. If you are passionate about cutting-edge AI/LLM technologies and enjoy driving Proof of Concept (POC) delivery, we are excited to invite you to apply! Your responsibilities will include collaborating with both business and technical teams to define and implement GenAI/ML use cases as POCs. You will be responsible for building and deploying ML/GenAI models on Google Vertex AI, fine-tuning and evaluating LLMs for real-world applications, working closely with data engineers to design secure and scalable ML pipelines, as well as documenting and maintaining reproducible workflows. To succeed in this role, you must possess 4-7 years of hands-on experience in ML/AI project delivery. A strong foundation in machine learning, deep learning, and LLMs is essential. Proficiency with Vertex AI tools such as AutoML, Pipelines, Model Registry, and GenAI Studio is required. Strong Python skills with knowledge of TensorFlow, PyTorch, Hugging Face, and scikit-learn are also crucial. Experience in prompt engineering, model tuning, and evaluation, along with excellent collaboration and communication skills across cross-functional teams, are key attributes we are looking for. Additionally, familiarity with PaLM, Gemini, or other open-source LLMs, knowledge of LangChain, experience with GCP services like BigQuery, Cloud Functions, Cloud Storage, proficiency in CI/CD for ML, and understanding of Docker/Kubernetes are considered as bonus skills. A background in media/OTT/Web platforms and experience with large-scale media datasets would be advantageous for this role.,

Greetings from Sun Technologies. Position: AI Engineer Years Of Experience: 5+ Years Work Location: HBR Layout, Bangalore (work from office) Job Type: Permanent/Fulltime Position Interview Mode : Virtual Shift Details: 12:30 PM TO 9:30 PM-IST (Free 2 ways cab with dinner) Roles Responsibilities: Strong background in traditional AI/ML Experience building GenAI chatbots, agents, implementing tools with Gemini or similar vendors Fine tuning experience of LLMs Ability to work with LLM APIs Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs) Agentic Frameworks (e.g., LangGraph, CrewAI, ). Experience with prompt engineering Experience with RAG architecture Experience in Google Cloud and Vertex AI Experienced with Python If interested please share updated resume to chandanap@suntechnologies.com, appreciate for references.

Key Responsibilities Design and implement machine learning models to address business challenges using structured and semi-structured data. Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects Develop and embed automated processes for predictive model validation, deployment, and implementation Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) Good hands-on skills in both feature engineering and hyperparameter optimization Experience producing high-quality code, tests, documentation Build end-to-end ML pipelines in collaboration with data engineering and product teams. Use Google Vertex AI components such as: Vertex Pipelines AutoML and Custom Training Vertex AI Workbench / Notebooks Vertex Feature Store Optimize model training, deployment, and monitoring workflows using MLOps best practices. Translate business requirements into analytical models with measurable outcomes. Required Skills 2-4 years of experience in data science and applied machine learning. Expertise in: Python, SQL, R, TensorFlow or PyTorch Feature engineering, model tuning, evaluation, and interpretation 1 year of experience working with Google Vertex AI or similar GCP ML tools. Strong grasp of machine learning concepts: supervised/unsupervised learning, recommendation engines, time series forecasting, etc. Exposure to BigQuery, Cloud Storage, or Dataflow for large-scale data manipulation. Preferred Skills Vertex AI Pipelines and Feature Store ML lifecycle automation and CI/CD for ML (MLflow, TFX, etc.) Docker, Airflow, or Cloud Composer for orchestration Google Cloud certifications (e.g., Professional Data Engineer, ML Engineer) are a plus. Interested candidates can share resume at- ashurustagi@kpmg.com

As a GCP Architect with AI Expertise, you will play a crucial role in leading the design, implementation, and optimization of cloud and AI-driven solutions on Google Cloud Platform (GCP). Your deep expertise in cloud infrastructure, AI/ML, networking, and security will be essential for architecting scalable, secure, and highly available cloud solutions while leveraging AI to drive automation and intelligence across enterprise environments. Your responsibilities will include designing and implementing scalable, secure, and cost-effective architectures on GCP, developing AI/ML-driven solutions using tools such as Vertex AI, BigQuery ML, TensorFlow, and AutoML, and architecting end-to-end data pipelines to support AI model training, deployment, and monitoring. You will also be responsible for building high-availability, backup, and disaster recovery solutions in GCP. In terms of infrastructure and security, you will implement identity management, IAM policies, security protocols, and network segmentation, design and automate provisioning of networks, firewalls, ACLs, and access control policies, and ensure compliance with security and governance frameworks for cloud-based AI workloads. Additionally, you will manage multi-VPC networking, hybrid cloud connectivity, and firewall configurations. Your role will also involve leading large-scale application and network migrations to GCP, developing Terraform-based infrastructure automation, and managing Infrastructure as Code (IaC). You will implement CI/CD pipelines for AI/ML workloads using tools like GitHub, Jenkins, and Ansible, and design DevOps solutions with cloud-native tools and containerized workloads on GKE. As a technical leader and advisor, you will provide strategic guidance on cloud adoption, AI/ML use cases, and infrastructure modernization, lead requirements gathering, solution design, and implementation for GCP cloud-based AI solutions, and support pre-sales activities, including POCs, RFP responses, and SOW creation. You will mentor and provide technical oversight to engineering teams and serve as a trusted cloud advisor for customers, helping them solve complex cloud infrastructure and AI challenges. Furthermore, you will be responsible for optimizing cloud resource usage, cost management, and AI model performance, conducting cloud usage analytics, security audits, and AI model monitoring, and developing strategies to improve network reliability, redundancy, and high availability. If you are passionate about cloud transformation, AI, and solving complex infrastructure challenges, this role presents a perfect opportunity for you to make a meaningful impact in the field of cloud and AI technologies.,

As a high-impact AI/ML Engineer, you will lead the design, development, and deployment of machine learning and AI solutions across vision, audio, and language modalities. You will be an integral part of a fast-paced, outcome-oriented AI & Analytics team, collaborating with data scientists, engineers, and product leaders to translate business use cases into real-time, scalable AI systems. Your responsibilities in this role will include architecting, developing, and deploying ML models for multimodal problems encompassing vision, audio, and NLP tasks. You will be responsible for the complete ML lifecycle, from data ingestion to model development, experimentation, evaluation, deployment, and monitoring. Leveraging transfer learning and self-supervised approaches where appropriate, you will design and implement scalable training pipelines and inference APIs using frameworks like PyTorch or TensorFlow. Collaborating with MLOps, data engineering, and DevOps teams, you will operationalize models using technologies such as Docker, Kubernetes, or serverless infrastructure. Continuously monitoring model performance and implementing retraining workflows to ensure sustained accuracy over time will be a key aspect of your role. You will stay informed about cutting-edge AI research and incorporate innovations such as generative AI, video understanding, and audio embeddings into production systems. Writing clean, well-documented, and reusable code to support agile experimentation and long-term platform development is an essential part of this position. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field, with a minimum of 5-8 years of experience in AI/ML Engineering, including at least 3 years in applied deep learning. In terms of technical skills, you should be proficient in Python, with knowledge of R or Java being a plus. Additionally, you should have expertise in ML/DL Frameworks like PyTorch, TensorFlow, and Scikit-learn, as well as experience in Computer Vision tasks such as image classification, object detection, OCR, segmentation, and tracking. Familiarity with Audio AI tasks like speech recognition, sound classification, and audio embedding models is also desirable. Strong capabilities in Data Engineering using tools like Pandas, NumPy, SQL, and preprocessing pipelines for structured and unstructured data are required. Knowledge of NLP/LLMs, Cloud & MLOps services, deployment & infrastructure technologies, and CI/CD & Version Control tools are also beneficial. Soft skills and competencies that will be valuable in this role include strong analytical and systems thinking, effective communication skills to convey models and results to non-technical stakeholders, the ability to work cross-functionally with various teams, and a demonstrated bias for action, rapid experimentation, and iterative delivery of impact.,

The primary responsibility of this role is to design, develop, and implement cutting-edge image and video generation systems leveraging deep learning models. You will take the lead in exploring and prototyping diffusion, GAN, and transformer-based architectures for generative tasks. Your expertise will be instrumental in optimizing models for quality, speed, and scalability through accelerated compute technologies such as CUDA and TensorRT. Collaboration with cross-functional teams including Product, Design, and Frontend will be essential to seamlessly integrate AI pipelines into production applications and platforms. Additionally, you will play a key role in contributing to system architecture, ensuring reproducibility, versioning, and model evaluation, while also staying updated on the latest advancements in generative AI to facilitate the transition from research and development to production. To excel in this role, you should possess a minimum of 2 years of hands-on experience in the field of AI/ML with a strong emphasis on generative models. Your track record should include practical experience with video generation models like Sora, Gen-2 by Runway, Synthesia, or custom pipelines. A solid background in image generation using Diffusion Models (e.g., Stable Diffusion, DALLE, Imagen) or GANs (e.g., StyleGAN2/3) is essential. Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, or JAX is required, along with experience in training large-scale models using multi-GPU setups like DDP, DeepSpeed, or Hugging Face Accelerate. A sound understanding of computer vision, image processing, and neural rendering techniques is crucial, as well as practical skills in model fine-tuning and related methodologies like LoRA/PEFT, ControlNet, DreamBooth, and others. Preferred tools and frameworks for this role include Stable Diffusion, DALLE, MidJourney, Sora, Gen-2, VQ-GAN, Pix2Pix, CycleGAN, AnimateDiff, ControlNet, T2I-Adapter, VideoCrafter, Pika Labs, ZeroScope, and ModelScope. Proficiency in FastAPI, Flask, or gRPC for model serving and Streamlit, Gradio, or React for rapid prototyping is advantageous. Experience with cloud platforms such as AWS, GCP, or Azure, particularly with GPU instances, and serving models using TorchServe, NVIDIA Triton, or Vertex AI, will be beneficial in ensuring scalable model deployment. This is a full-time position with a flexible schedule and a day shift from Monday to Friday. The ideal candidate will have a minimum of 2 years of experience in machine learning. The work location is in person, and the expected start date is 01/08/2025.,

Hi, Greetings from Sun Technology Integrators!! This is regarding a job opening with Sun Technology Integrators, Bangalore. Please find below the job description for your reference. Kindly let me know your interest and share your updated CV to nandinis@suntechnologies.com ASAP. Strong background in traditional AI/ML Experience building GenAI chatbots, agents, implementing tools with Gemini or similar vendors Fine tuning experience of LLMs Ability to work with LLM APIs Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs) Agentic Frameworks (e.g., LangGraph, CrewAI, ). Experience with prompt engineering Experience with RAG architecture Experience in Google Cloud and Vertex AI Experienced with Python Please let me know, if any of your friends are looking for a job change. Kindly share the references. Please Note: WFO- Work From Office (No hybrid or Work From Home) Shift Details: IST Shift - 12.30 PM to 9.30 PM IST -2 ways free cab facility(Pickup+Drop) Years of Exp-5 to 10 years Interview Mode- 2 rounds Virtual interview Thanks and Regards, Nandini S | Sr.Technical Recruiter Sun Technology Integrators Pvt. Ltd. nandinis@suntechnologies.com www.suntechnologies.com

Responsibilities: * Design, develop & deploy generative AI models using ML algorithms on GCP cloud. * Optimize model performance through data analysis & experimentation.