13 Automl Jobs

As an experienced professional with over 5 years of expertise in AI, Cloud Architecture (with a strong emphasis on Azure), and Global SaaS/AI/AgTech Startups, you have the opportunity to shape the future of AI-Driven Agriculture in a high-impact, senior role based in Gurugram, IN. In this role, you will be responsible for architecting scalable AI, IoT, and cloud solutions that contribute to sustainable farming practices. Working closely with the Founder & CEO, CTO, and AI/IoT teams, you will play a pivotal role in defining and executing a global-ready Azure AI-Cloud architecture. Your expertise will be instrumental in expanding the global market presence of AI-driven vertical farms & Agritech platforms into markets such as SEA, UAE, and the US. Your primary responsibilities will include architecting and scaling INNOFarms.AI's AI-powered cloud platform on Azure, optimizing AI-driven data pipelines for real-time farm monitoring, decision-making, and automation, integrating IoT, Robotics, and AI models into a scalable Cloud & Edge Computing framework, and enhancing cybersecurity, compliance, and data privacy measures for global markets. Additionally, you will provide strategic technical direction, guide engineering teams in India(Gurugram) and HK, and collaborate closely with the Founder & CEO/VCs & business teams to align tech strategy with fundraising & global expansion efforts. To excel in this role, you should bring to the table a minimum of 7 years of experience in AI, Cloud, SaaS, or IoT product scaling, deep expertise in Azure technologies such as Deep Azure IoT hub, AI, Event Hubs, CosmosDB, and Serverless Functions, hands-on experience in AI model deployment using tools like ML Ops, TensorFlow, PyTorch, and AutoML, as well as prior experience in scaling AI/SaaS startups globally, particularly in the Middle East, SEA, and US markets. Leadership experience in AI-AgTech or AI Venture would be advantageous, along with a strong ability to mentor remote, distributed engineering teams. Experience in AgriTech, IoT, or Smart Automation Platforms, as well as an understanding of regulatory, security, and compliance requirements for AI-based cloud systems, would be considered a plus for this role. If you are ready to take on this exciting opportunity and contribute to the advancement of AI-driven agriculture, we encourage you to apply by sending your resume to Careers@INNOFarms.ai.,

You are a highly skilled AI/ML/Gen AI Data Scientist with expertise in Generative AI, Machine Learning, Deep Learning, and Natural Language Processing (NLP). You have a strong foundation in Python-based AI frameworks and experience in developing, deploying, and optimizing AI models for real-world applications. Your responsibilities include developing and implementing AI/ML models, working with Deep Learning architectures like Transformers (BERT, GPT, LLaMA) and CNNs/RNNs, fine-tuning and optimizing Large Language Models (LLMs) for various applications, designing and training custom Machine Learning models using structured and unstructured data, leveraging NLP techniques such as text summarization and Named Entity Recognition (NER), implementing ML pipelines, and deploying models in cloud environments (AWS/GCP/Azure). You will collaborate with cross-functional teams to integrate AI-driven solutions into business applications and stay updated with the latest AI advancements to apply innovative techniques to improve model performance. To qualify for this role, you should have 1 to 3 years of experience in AI/ML, Deep Learning, and Generative AI, strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn, hands-on experience with NLP models including BERT, GPT, T5, LLaMA, and Stable Diffusion, expertise in data preprocessing, feature engineering, and model evaluation, experience with MLOps, cloud-based AI deployment, and containerization (Docker, Kubernetes), knowledge of vector databases and retrieval-augmented generation (RAG) techniques, ability to fine-tune LLMs and work with prompt engineering, strong problem-solving skills, and the ability to work in agile environments. You should hold a Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, or Information Technology. Preferred skills include experience with Reinforcement Learning (RLHF) and multi-modal AI, familiarity with AutoML, Responsible AI (RAI), and AI Ethics, exposure to Graph Neural Networks (GNNs) and time-series forecasting, contributions to open-source AI projects or research papers. Your skills should encompass Machine Learning (ML), Generative AI, Artificial Intelligence (AI), Python, and Large Language Models (LLM).,

You will be working as a Lead Data Engineer & Architect at Phonologies, a company that specializes in managing telephony infrastructure for contact center applications and chatbots. Phonologies" platform is utilized by leading pharmacy chains, Fortune 500 companies, and North America's largest carrier to automate voice-based customer support queries, enhancing customer interactions and operational efficiencies. The company is headquartered in India and operates on a global scale. As the Lead Data Engineer & Architect, your role will involve designing and implementing data architecture, creating and maintaining data pipelines, performing data analysis, and collaborating with different teams to enhance data-driven decision-making processes. You will also be tasked with leading data engineering projects, ensuring data quality and security, and leveraging your expertise to drive successful outcomes. To be successful in this role, you should possess at least 10 years of experience in enterprise data engineering and architecture. You must be proficient in ETL processes, orchestration, and streaming pipelines, with a strong skill set in technologies such as Hadoop, Spark, Azure, Kafka, and Kubernetes. Additionally, you should have a track record of building MLOps and AutoML-ready production pipelines and delivering solutions for telecom, banking, and public sector industries. Your ability to lead cross-functional teams with a focus on client satisfaction will be crucial, as well as your certifications in data platforms and AI leadership. If you are passionate about data engineering, architecture, and driving innovation in a dynamic environment, this role at Phonologies may be the perfect opportunity for you. Join our team in Pune and contribute to our mission of revolutionizing customer support through cutting-edge technology solutions.,

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.,

You should have the ability to work with large data sets using Python and possess a strong background in Python programming, MySQL, Linux, and Machine Learning. It is essential to have basic knowledge of other relevant technologies such as Cloud computing, Jupyter Notebook, Machine learning algorithms, TensorFlow, PyTorch, Tesseract OCR, and NLP techniques including models like SpaCy, Bert, NLTK, and AutoML. You will be required to work through the phases of the project. This is a full-time job that requires you to work in person. The interview will be conducted in person, and there are no telephonic interviews scheduled. The job follows a Day shift and Morning shift schedule. A Bachelor's degree is preferred for this role. Additionally, having 1 year of experience in C++ is required for this position.,

As a Senior Data Scientist with a focus on Predictive Analytics and expertise in Databricks, your primary responsibilities will involve designing and implementing predictive models for various applications such as forecasting, churn analysis, and fraud detection. You will utilize tools like Python, SQL, Spark MLlib, and Databricks ML to deploy these models effectively. Your role will also include building end-to-end machine learning pipelines on the Databricks Lakehouse platform, encompassing data ingestion, feature engineering, model training, and deployment. It will be essential to optimize model performance through techniques like hyperparameter tuning, AutoML, and leveraging MLflow for tracking. Collaboration with engineering teams will be a key aspect of your job to ensure the operationalization of models, both in batch and real-time scenarios, using Databricks Jobs or REST APIs. You will be responsible for implementing Delta Lake to support scalable and ACID-compliant data workflows, as well as enabling CI/CD for machine learning pipelines using Databricks Repos and GitHub Actions. In addition to your technical duties, troubleshooting Spark Jobs and resolving issues within the Databricks Environment will be part of your routine tasks. To excel in this role, you should possess 3 to 5 years of experience in predictive analytics, with a strong background in regression, classification, and time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark is crucial for success in this position. Familiarity with tools like MLflow, Feature Store, and Unity Catalog for governance purposes will be advantageous. Industry experience in Life Insurance or Property & Casualty (P&C) is preferred, and holding a certification as a Databricks Certified ML Practitioner would be considered a plus. Your technical skill set should include proficiency in Python, PySpark, MLflow, and Databricks AutoML. Expertise in predictive modeling techniques such as classification, clustering, regression, time series analysis, and NLP is required. Familiarity with cloud platforms like Azure or AWS, Delta Lake, and Unity Catalog will also be beneficial for this role.,

As an Artificial Intelligence Specialist at Gen AI, you will be responsible for driving customer conversations, understanding customer requirements, creating Gen AI solution architectures, and developing customer proposals and RFP responses. You will guide solution engineers in creating Gen AI POCs and solutions for various industry verticals. Your role will involve staying updated on the latest technology developments, industry best practices, and incorporating them into Gen AI applications. Additionally, you will design and deploy Proof of Concepts (POCs) and Points of View (POVs) across different industry verticals to showcase the potential of Generative AI applications. To qualify for this role, you should have at least 8 years of experience in software development, with a minimum of 3 years of experience in Generative AI solution development. A bachelor's degree or higher in Computer Science, Software Engineering, or related fields is required. You should be adept at critical thinking, logical reasoning, and have a strong ability to learn new industry domains quickly. Being a team player who can deliver under pressure is essential. Furthermore, you should have experience with cloud technologies such as Azure, AWS, or GCP, as well as a good understanding of NVIDIA or similar technologies. A solid appreciation of AI/ML concepts and sound design principles is necessary for this role. In terms of required skills, you should be extremely dynamic and enthusiastic about technology. Development experience with languages like C++, Java, JavaScript, HTML, C#, Python, or node.js is preferred. You should be able to adapt quickly to new challenges and evolving technology stacks. Excellent written and verbal communication skills in English are essential, along with strong analytical and critical thinking abilities. A customer-focused attitude, initiative-taking, self-driven nature, and the ability to learn quickly are also important qualities for this role. Knowledge of Python, ML Algorithms, Statistics, source code maintenance, versioning tools, Object-Oriented Programming Concepts, debugging, and analytical skills is required. Preferred skills for this position include at least 5 years of experience in ML development and MLOps. Strong programming skills in Python, knowledge of ML, Data, and API libraries, and expertise in creating end-to-end data pipelines are advantageous. Experience with ML models, ModelOps/MLOps, AutoML, AI Ethics, Trust, Explainable AI, and popular ML frameworks like SparkML, TensorFlow, scikit-learn, XGBoost, H2O, etc., is beneficial. Familiarity with working in cloud environments (AWS, Azure, GCP) or containerized environments (Mesos, Kubernetes), interest in understanding functional and industry business challenges, and knowledge of IT industry and GenAI use cases in insurance processes are preferred. Expertise in Big Data and Data Modeling is also desirable for this role.,

You will be working as a Databricks Developer with 3-6 years of experience, located in India. Joining the data engineering and AI innovation team, your main responsibilities will include developing scalable data pipelines using Databricks and Apache Spark, implementing AI/ML workflows with tools like MLflow and AutoML, collaborating with data scientists to deploy models into production, performing ETL development, data transformation, and model training pipelines, managing Delta Lake architecture, and working closely with cross-functional teams to ensure data quality and governance.,

You should have a strong understanding of the tech stack including GCP Services such as BigQuery, Cloud Dataflow, Pub/Sub, Dataproc, and Cloud Storage. Experience with Data Processing tools like Apache Beam (batch/stream), Apache Kafka, and Cloud Dataprep is crucial. Proficiency in programming languages like Python, Java/Scala, and SQL is required. Your expertise should extend to Orchestration tools like Apache Airflow (Cloud Composer) and Terraform, and Security aspects including IAM, Cloud Identity, and Cloud Security Command Center. Knowledge of Containerization using Docker and Kubernetes (GKE) is essential. Familiarity with Machine Learning platforms such as Google AI Platform, TensorFlow, and AutoML is expected. Candidates with certifications like Google Cloud Data Engineer and Cloud Architect are preferred. You should have a proven track record of designing scalable AI/ML systems in production, focusing on high-performance and cost-effective solutions. Strong experience with cloud platforms (Google Cloud, AWS, Azure) and cloud-native AI/ML services like Vertex AI and SageMaker is important. Your role will involve implementing MLOps practices, including model deployment, monitoring, retraining, and version control. Leadership skills are key to guide teams, mentor engineers, and collaborate effectively with cross-functional teams to achieve business objectives. A deep understanding of frameworks like TensorFlow, PyTorch, and Scikit-learn for designing, training, and deploying models is necessary. Experience with data engineering principles, scalable pipelines, and distributed systems (e.g., Apache Kafka, Spark, Kubernetes) is also required. Nice to have requirements include strong leadership and mentorship capabilities to guide teams towards best practices and high-quality deliverables. Excellent problem-solving skills focusing on designing efficient, high-performance systems are valued. Effective project management abilities are necessary to handle multiple initiatives and ensure timely delivery. Collaboration and teamwork are emphasized to foster a positive and productive work environment.,

Job Title : Data Scientist Location State : Tamil Nadu,Telangana Location City : Hyderabad, Chennai Experience Required : 4 to 6 Year(s) CTC Range : 7 to 11 LPA Shift: Day Shift Work Mode: Onsite Position Type: C2H Openings: 2 Company Name: VARITE INDIA PRIVATE LIMITED About The Client: Client is an Indian multinational technology company specializing in information technology services and consulting. Headquartered in Mumbai, it is a part of the Tata Group and operates in 150 locations across 46 countries. About The Job: Requirements: 5+ years in predictive analytics, with expertise in regression, classification, time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark. Familiarity with MLflow, Feature Store, and Unity Catalog for governance. Industry experience in Life Insurance or P&C. Skills: Python, PySpark , MLflow, Databricks AutoML. Predictive MoClienting (Classification , Clustering , Regression, timeseries and NLP). Cloud platform (Azure/AWS) , Delta Lake, Unity Catalog. Certifications; Databricks Certified ML Practitioner (Optional) Essential Job Functions: Design and deploy predictive models (e.g., forecasting, churn analysis, fraud detection) using Python/SQL, Spark MLlib, and Databricks ML. Build end-to-end ML pipelines (data ingestion, feature engineering, model training, deployment) on Databricks Lakehouse. Optimize model performance via hyperparameter tuning, AutoML, and MLflow tracking. Collaborate with engineering teams to operationalize models (batch/real-time) using Databricks Jobs or REST APIs. Implement Delta Lake for scalable, ACID-compliant data workflows. Enable CI/CD for ML pipelines using Databricks Repos and GitHub Actions. Troubleshoot issues in Spark Jobs and Databricks Environment. Qualifications: Skill Required: Data Science, Python for Data Science Experience Range in Required Skills: 4-6 Years How to Apply: Interested candidates are invited to submit their resume using the apply online button on this job post. About VARITE: VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services. Equal Opportunity Employer: VARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status. Unlock Rewards: Refer Candidates and Earn. If you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the referred candidate completes a three-month assignment with VARITE. Exp Req - Referral Bonus 0 - 2 Yrs. - INR 5,000 2 - 6 Yrs. - INR 7,500 6 + Yrs. - INR 10,000

Looking for an ML Engineer to design & implement AI/ML models using Python, TensorFlow, PyTorch, Scikit-learn. Optimise models, run experiments, transform data via classification/clustering, and stay updated on the latest AI/ML advancements. Required Candidate profile 3+ years of exp in AI/ML & Python Experience in TensorFlow, PyTorch, scikit-learn, Keras, AutoML, AI Clouds (H2O, AWS) Good in Data Structures, OOPS, TDD Perks and benefits Visit our Company website

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients . Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. I nviting applications for the role of AM, Data Scientist Today, the world is operating in a more dynamic market, with more capable competitors than ever before. To meet our ambitions for democratizing access to the digital economy and financial services, we need to play our very best game. That&rsquos why transforming the business to be more customer-centric and global in mindset to solve customer problems. Alongside Sales and Product functions, the Marketing function will be central to this transformation. With an ambition to create and embed a bold new operating model that will position us to compete and win in the market. It will empower marketers on the frontline and our Marketing function more broadly with the knowledge, skills, platforms, and capabilities to do exceptional work. Responsibilities Participate and collaborate with Sales and Marketing teams in the organization to understand the business requirements and to deliver scalable solutions Analyze user behavior, conversion data, customer journeys to generate hypotheses and build optimization plans and provide insights for feature improvements Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies Continuously think about how to improve the analytics infrastructure for the team and automate processes Perform deep-dive analyses on key business trends from different perspectives and package the insights into easily consumable presentations and documents Provide thought leadership within the marketing analytics community Qualification we seek in you! Minimum Qualifications /skills Education in Statistics, Mathematics, Computer Science, or another quantitative field . Relevant working experience Knowledge of a variety of machine learning and Statistical techniques (Regression, Statistical Tests, Properties of distributions, Clustering, CART, SVM, etc.) and their real-world advantages/drawbacks. Experience using computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets. Experience in creating AI/ML models for Marketing use cases Experience in using industry-standard AI/ML libraries i.e. Sklearn , Keras , Tensorflow , AutoML , etc. Experience in working on Marketing Analytics Excellent communication & presentation skills Good exposure in the Marketing analytics domain for a Fintech-based client and should be able to break the problem into small chunks Ability to create models using Classification and Regression techniques and perform Hypothesis Testing and Feature selection Ability to use creativity to spot trends and tease out patterns in large datasets Good analytical and problem-solving skills, and ability to set goals and meet deadlines in a fast-paced working environment Preferred Qualification s/skills Knowledge of Hadoop/Hive is good to have 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. Get to know us at www.genpact.com and on , Facebook, LinkedIn, and YouTube. 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.

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.