Required Experience: 7 to 10 Years Preferred Immediate Joiner Apply now We are seeking an experienced and dynamic Lead Data Engineer to join our team. This role is pivotal in advancing our data engineering practices on the Google Cloud Platform (GCP) and offers a unique opportunity to work with cutting-edge technologies, including Generative AI. Key Responsibilities: Lead the design, implementation, and optimization of scalable data pipelines and architectures on GCP using key services such as Big Query, Dataflow, Pub/Sub, and Cloud Storage. Collaborate with cross-functional teams to define data requirements and develop strategic solutions that address business needs. Enhance existing data infrastructure, ensuring high levels of performance, reliability, and security. Drive the integration and deployment of machine learning models and advanced analytics solutions, incorporating Generative AI where applicable. Establish and enforce best practices in data governance, data quality, and data security. Mentor and guide junior engineers, fostering a culture of innovation and continuous improvement. Stay informed about the latest trends in data engineering, GCP advancements, and Generative AI technologies to drive innovation within the team. Required Skills Qualifications: Bachelor s or master s degree in computer science, Information Technology, or a related field. 7+ to 10 years of experience in data engineering, with a strong emphasis on GCP technologies. Demonstrated expertise in building and managing data solutions using GCP services like Big Query, Dataflow, and Cloud Composer. Proficiency in SQL and programming languages such as Python, Java, or Scala. Strong understanding of data modelling, warehousing concepts, and real-time data processing. Familiarity with containerization and orchestration tools like Docker and Kubernetes. Excellent analytical, problem-solving, and communication skills. Leadership experience with a proven ability to mentor and develop junior team members. Preferred Qualifications: GCP Professional Data Engineer certification. Experience with Generative AI technologies and their practical applications. Knowledge of additional cloud platforms such as AWS or Azure. Experience with implementing data governance frameworks and tools. Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit

Required Experience: 7 to 10 Years Preferred Immediate Joiner Apply now We are looking for an accomplished Lead Data Engineer with expertise in Databricks to join our dynamic team. This role is crucial for enhancing our data engineering capabilities, and it offers the chance to work with advanced technologies, including Generative AI. Key Responsibilities: Lead the design, development, and optimization of data solutions using Databricks, ensuring they are scalable, efficient, and secure. Collaborate with cross-functional teams to gather and analyse data requirements, translating them into robust data architectures and solutions. Develop and maintain ETL pipelines, leveraging Databricks and integrating with Azure Data Factory as needed. Implement machine learning models and advanced analytics solutions, incorporating Generative AI to drive innovation. Ensure data quality, governance, and security practices are adhered to, maintaining the integrity and reliability of data solutions. Provide technical leadership and mentorship to junior engineers, fostering an environment of learning and growth. Stay updated on the latest trends and advancements in data engineering, Databricks, Generative AI, and Azure Data Factory to continually enhance team capabilities. Required Skills Qualifications: Bachelor s or master s degree in computer science, Information Technology, or a related field. 7+ to 10 years of experience in data engineering, with a focus on Databricks. Proven expertise in building and optimizing data solutions using Databricks and integrating with Azure Data Factory/AWS Glue. Proficiency in SQL and programming languages such as Python or Scala. Strong understanding of data modelling, ETL processes, and Data Warehousing/Data Lakehouse concepts. Familiarity with cloud platforms, particularly Azure, and containerization technologies such as Docker. Excellent analytical, problem-solving, and communication skills. Demonstrated leadership ability with experience mentoring and guiding junior team members. Preferred Qualifications: Experience with Generative AI technologies and their applications. Familiarity with other cloud platforms, such as AWS or GCP. Knowledge of data governance frameworks and tools. Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit

Required Experience: 5 to 8 Years Preferred Immediate Joiner Apply now We are looking for a Senior AI/ML Engineer to develop, deploy, and optimize AI-driven solutions. This role requires expertise in machine learning, deep learning, and Generative AI, with a strong focus on implementing cutting-edge AI models for business applications. Key Responsibilities: Develop and deploy AI/ML models to solve complex business problems. Design and optimize Generative AI models for various applications. Perform data preprocessing, feature engineering, and model tuning to enhance accuracy. Collaborate with cross-functional teams to integrate AI solutions into existing workflows. Conduct research and stay updated on the latest advancements in AI, ML, and LLMs. Implement MLOps best practices to ensure scalable and efficient model deployment. Mentor junior engineers and contribute to knowledge sharing. Present technical findings and project results to stakeholders. Required Skills Qualifications: Bachelor s or master s degree in computer science, AI, ML, or a related field. 5 to 8 years of hands-on experience in AI/ML development. Strong proficiency in Python, R, or Java , along with ML frameworks like TensorFlow, PyTorch, or Keras . Expertise in Generative AI, NLP, and deep learning techniques . Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). Experience with MLOps tools for model lifecycle management. Strong analytical and problem-solving skills. Excellent communication skills for collaboration with business teams. Preferred Qualifications: Experience with multi-agent systems and Generative AI design patterns . Understanding of computer vision, reinforcement learning , and AI-driven automation. Contributions to AI research, publications, or open-source projects. Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit

Position: Lead AI Engineer Location: Ahmedabad, Pune Required Experience: 8+ Years Preferred Immediate Joiner Apply now We are seeking an experienced Lead AI Engineer to spearhead AI initiatives, drive innovation, and architect scalable AI/ML solutions. This role involves leading AI-driven projects, mentoring teams, and integrating AI solutions into enterprise applications. Key Responsibilities: Architect and develop enterprise-scale AI/ML solutions , including Generative AI and LLMs. Lead research and implementation of cutting-edge AI methodologies. Collaborate with business stakeholders to define AI strategy and align it with business goals. Optimize model performance and scalability for production deployment. Establish best practices for AI development, including MLOps and model monitoring . Drive innovation by exploring new AI techniques and frameworks. Manage and mentor a team of AI engineers, fostering a culture of continuous learning. Present insights, research findings, and AI-driven solutions to leadership teams. Required Skills Qualifications: Master s or Ph.D. in Computer Science, AI, Machine Learning, or a related discipline. 8+ years of experience in AI, ML, and deep learning, with a track record of successful AI deployments. Strong expertise in LLMs, Generative AI, NLP, and multimodal AI . Proficiency in Python, R, Java , and AI/ML frameworks like TensorFlow, PyTorch, or Hugging Face . Extensive experience with cloud-based AI solutions, MLOps, and scalable architectures . Ability to lead AI-driven initiatives and collaborate with cross-functional teams. Strong leadership skills to manage, mentor, and guide engineering teams. Excellent communication and stakeholder management abilities. Preferred Skills: Experience in multi-agent systems, federated learning, and AI ethics . Understanding of computer vision, reinforcement learning, and AI automation . Contributions to AI research, patents, or high-impact publications . Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit

Required Experience: 5+ Years Preferred Immediate Joiner Apply now Building the machine learning production infrastructure (or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. We are looking for a highly skilled MLOps Engineer to join our team. As an MLOps Engineer, you will be responsible for designing, implementing, and maintaining the infrastructure that supports the deployment, monitoring, and scaling of machine learning models in production. You will work closely with data scientists, software engineers, and DevOps teams to ensure seamless integration of machine learning models into our production systems. The job is NOT for your if You don t want to build a career in AI/ML. Becoming an expert in this technology and staying current will require significant self-motivation. You like the comfort and predictability of working on the same problem or code base for years. The tools, best practices, architectures, and problems are all going through rapid change you will be expected to learn new skills quickly and adapt. Key Responsibilities: Model Deployment: Design and implement scalable, reliable, and secure pipelines for deploying machine learning models to production. Infrastructure Management: Develop and maintain infrastructure as code (IaC) for managing cloud resources, compute environments, and data storage. Monitoring and Optimization: Implement monitoring tools to track the performance of models in production, identify issues, and optimize performance. Collaboration: Work closely with data scientists to understand model requirements and ensure models are production ready. Automation: Automate the end-to-end process of training, testing, deploying, and monitoring models. Continuous Integration/Continuous Deployment (CI/CD): Develop and maintain CI/CD pipelines for machine learning projects. Version Control: Implement model versioning to manage different iterations of machine learning models. Security and Governance: Ensure that the deployed models and data pipelines are secure and comply with industry regulations. Documentation: Create and maintain detailed documentation of all processes, tools, and infrastructure. Qualifications: 5+ years of experience in a similar role (DevOps, DataOps, MLOps, etc.) Bachelor s or master s degree in computer science, Engineering, or a related field. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) Strong understanding of machine learning lifecycle, data pipelines, and model serving. Proficiency in programming languages such as Python, Shell scripting, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.). Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) Experience with CI/CD tools like Jenkins, GitLab CI, or similar Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent) Strong software engineering skills in complex, multi-language systems Comfort with Linux administration Experience working with cloud computing and database systems Experience building custom integrations between cloud-based systems using APIs Experience developing and maintaining ML systems built with open-source tools Experience developing with containers and Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (MLFlow, KubeFlow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology and best practices Understanding of regulatory requirements for data privacy and model governance. Good to Have: Excellent problem-solving skills and ability to troubleshoot complex production issues. Strong communication skills and ability to collaborate with cross-functional teams. Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). Knowledge of database systems (SQL, NoSQL). Experience with Generative AI frameworks. Preferred cloud-based or MLOps/DevOps certification (AWS, GCP, or Azure). Perks: Flexible Timings 5 Days Working Healthy Environment Celebration Learn and Grow Build the Community Medical Insurance Benefit