17 Lightgbm Jobs

???? Were Hiring: AI Engineer ???? Location: Bengaluru (Regular office-based role) ???? Employment Type: Full-Time | 5 Days a Week from Office ???? Qualification: B.E / B.Tech or equivalent degree in Computer Science, IT, or related field Are you passionate about building and scaling production-grade AI/ML systems We&aposre looking for a skilled AI Engineer to join our team in Bengaluru and help drive real-world impact through cutting-edge machine learning and GenAI technologies. ???? Must-Have Skills: 48 years of hands-on experience in designing, building, and deploying production-grade AI/ML solutions Proficiency in Python, PySpark, SQL , and ML libraries like Scikit-learn, XGBoost, LightGBM Cloud-native ML development experience on AWS (SageMaker), GCP (Vertex AI), or Azure ML Strong background in NLP/GenAI frameworks: Hugging Face, LangChain, LlamaIndex Practical knowledge of MLOps tools (MLflow, Weights & Biases, DVC) and deployment frameworks ( FastAPI, Flask, Docker, Kubernetes ) Excellent communication, stakeholder engagement, and team collaboration skills Good-to-Have: Publications, blog posts, or open-source contributions in AI/ML Experience leading AI strategy or owning technical roadmaps Show more Show less

House of Shipping is seeking a high-caliber Data Science Lead to join their team in Hyderabad. With a background of 15-18 years in data science, including at least 5 years in leadership roles, the ideal candidate will have a proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing. Strong expertise in statistical learning, ML architecture, productionizing models, and impact tracking is essential for this role. As the Data Science Lead, you will be responsible for leading enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This position requires a blend of technical leadership and strategic alignment with various business units to deliver measurable business impact. Key responsibilities include defining and driving the data science roadmap across forecasting, route optimization, warehouse simulation, inventory management, and fraud detection. You will work closely with engineering teams to architect end-to-end pipelines, from data ingestion to API deployment. Proficiency in Python and MLOps tools like Scikit-Learn, XGBoost, PyTorch, MLflow, Vertex AI, or AWS SageMaker is crucial for success in this role. Collaboration with operations, product, and technology teams to prioritize AI use cases and define business metrics will be a key aspect of the job. Additionally, you will be responsible for managing experimentation frameworks, mentoring team members, ensuring model validation, and contributing to organizational data maturity. The ideal candidate will possess a Bachelor's, Master's, or Ph.D. degree in Computer Science, Mathematics, Statistics, or Operations Research. Certifications in Cloud ML stacks, MLOps, or Applied AI are preferred. To excel in this role, you should have a strategic vision in AI applications across the supply chain, strong team mentorship skills, expertise in statistical and ML frameworks, and experience in MLOps pipeline management. Excellent business alignment and executive communication skills are also essential for this position. If you are a data science leader looking to make a significant impact in the logistics industry, we encourage you to apply for this exciting opportunity with House of Shipping.,

Aarki is an AI company dedicated to developing advertising solutions that drive mobile revenue growth. Utilizing AI technology, we identify audiences in a privacy-first environment by analyzing trillions of contextual bidding signals alongside our proprietary behavioral models. Our comprehensive audience engagement platform consists of a full-service agency team and a Unified Creative Strategy that offers ad creative ideation and execution services. With a history of working with numerous advertisers over 14 years, we process 5 million mobile ad requests per second from over 10 billion devices, effectively enhancing performance for publishers and brands. Headquartered in San Francisco, CA, we also maintain offices in the United States, EMEA, and APAC. We are currently looking for a dynamic and detail-oriented Senior Manager of Applied Data Science to join our team. As a Senior Manager, you will lead a team responsible for creating and implementing machine learning models and data pipelines to optimize our programmatic demand-side platform (DSP). Collaborating closely with decision science, engineering, and analytics teams, you will drive impactful data science projects and contribute to innovative solutions. Join us in our mission to push the boundaries of AI and mobile advertising within a collaborative environment that encourages creativity and growth. At Aarki, we offer a competitive salary, comprehensive benefits, and substantial opportunities for career advancement. Responsibilities include: - Building, nurturing, and mentoring a high-performing data science team, emphasizing technical growth and long-term career development. - Spearheading the development of scalable machine learning pipelines tailored for programmatic mobile advertising. - Establishing best practices for model deployment, monitoring, and performance assessment. - Taking ownership of process enhancements throughout the ML lifecycle. - Promoting collaboration with teams in Bangalore and San Francisco, including decision science and bidder engineering, to deploy models into production and conduct experiments. - Ensuring timely project deliveries and swift resolution of model-related issues in production environments. - Designing and managing data pipelines to facilitate the efficient processing of large-scale datasets for training and evaluation. - Collaborating with product managers, engineers, and business stakeholders to seamlessly integrate models into production systems. - Staying abreast of advancements in machine learning and applying cutting-edge techniques to enhance platform capabilities. - Driving innovation by exploring and adopting new methodologies, tools, and technologies. The ideal candidate possesses: - Over 7 years of hands-on experience in data science, with a solid background in machine learning, statistics, and modeling. - More than 3 years of experience in managing teams of data scientists or ML engineers. - Proficiency in Python and SQL, with familiarity in Spark being advantageous. - Expertise in ML libraries like Scikit-Learn, LightGBM, TensorFlow, and PyTorch. - Profound understanding of probability, statistical analysis, and experimental design. - Demonstrated expertise in deploying ML models into production and ensuring continuous model observability. - Exceptional communication skills enabling the effective explanation of complex concepts to both technical and non-technical audiences. - Knowledge of RTB, auction theory, and high-throughput low-latency environments is a plus.,

The ML Solutions team within Markets OPS Technology is dedicated to developing solutions using Artificial Intelligence, Machine Learning, and Generative AI. This team is a leader in creating new ideas, innovative technology solutions, and ground-breaking solutions for Markets Operations and Other Line of Businesses. We work closely with our clients and business partners to progress solutions from ideation to production by leveraging the entrepreneurial spirit and technological excellence. The ML Solutions team is seeking a Data Scientist/Machine Learning Engineer to drive the design, development, and deployment of innovative AI/ML and GenAI-based solutions. In this hands-on role, you will leverage your expertise to create a variety of AI models, guiding a team from initial concept to successful production. A key aspect involves mentoring team members and fostering their growth. You will collaborate closely with business partners and stakeholders, championing the adoption of these advanced technologies to enhance client experiences, deliver tangible value to our customers, and ensure adherence to regulatory requirements through cutting-edge technical solutions. This position offers a unique opportunity to shape the future of our AI initiatives and make a significant impact on the organization. Key Responsibilities: - Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks. - Mentoring Young Talents: Mentoring team, guiding data analysts/ML engineers from concept to production. This involves fostering technical growth, providing project oversight, and ensuring adherence to best practices, ultimately building a high-performing and innovative team. - Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation. - Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field. - Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services. Skills & Qualifications: - 8 to 13 years of Strong hands-on experience in Machine Learning, delivering complex solutions to production. - Experience with Generative AI technologies essential. - Understanding of concepts like supervised, unsupervised, clustering, embedding. - Knowledge of NLP, Name Entity Recognition, Computer Vision, Transformers, Large Language Models. - In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar. - Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy, OpenCV. - Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch, Keras. - Proficiency in Python Software Development, following Object-Oriented design patterns and best practices. - Strong background in mathematics: linear algebra, probability, statistics, and optimization. - Experience with evaluation, scoring with a framework like ML Flow - Experience of Docker container and edited a Docker file, experience with K8s is a plus. - Experience with Postgres and Vector DBs a plus. - Excellent problem-solving skills and the ability to think creatively. - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - Publications and contributions to the AI research community are a plus. - Masters degree/Ph. D. or equivalent experience in Computer Science, Data Science, Statistics, or a related field. - 8-12 years of experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.,

As a Senior Data Scientist specializing in Generative AI at our organization, you will play a crucial role in driving technical innovation and delivering impactful results within a team setting. You will be responsible for working with financial data, applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and troubleshooting and debugging GenAI models in production. To excel in this role, you must possess a Master's degree in Computer Science, Data Science, or a related field, with a Ph.D. being preferred. You should have 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI. Additionally, you should have demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. You must stay up-to-date with the rapidly evolving GenAI landscape, continuously learn and explore new tools and techniques, and effectively communicate technical concepts to non-technical stakeholders. Proficiency in Python, along with expertise in key libraries for AI/ML and GenAI applications such as TensorFlow, PyTorch, and Transformers, is mandatory. Experience in designing and implementing scalable API architectures for GenAI applications, along with a deep understanding of Machine Learning concepts, is essential. Preferred qualifications for this role include experience with MLOps, cloud computing platforms, conversational AI solutions, and contributions to research and publications in the field of Generative AI. As a Senior Data Scientist, you will be expected to demonstrate strong technical leadership and mentorship skills, as well as excellent communication and collaboration abilities. This job description provides a comprehensive overview of the responsibilities and qualifications required for the Senior Data Scientist position. If you are a highly motivated individual with a strong passion for Generative AI and possess the necessary technical skills and experience, we encourage you to apply for this role.,

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

Job Summary: We are looking for a highly skilled and experienced AI/ML Developer-Lead with 4-5 years of hands-on relevant experience to join our technology team. You will be responsible for designing, developing, and optimizing machine learning models that drive intelligent business solutions. The role involves close collaboration with cross-functional teams to deploy scalable AI systems and stay abreast of evolving trends in artificial intelligence and machine learning. Key Responsibilities: 1. Develop and Implement AI/ML Models Design, build, and implement AI/ML models tailored to solve specific business challenges, including but not limited to natural language processing (NLP), image recognition, recommendation systems, and predictive analytics. 2. Model Optimisation and Evaluation Continuously improve existing models for performance, accuracy, and scalability. 3. Data Preprocessing and Feature Engineering Collect, clean, and preprocess structured and unstructured data from various sources. Engineer relevant features to improve model performance and interpret ability. 4. Collaboration and Communication Collaborate closely with data scientists, back end engineers, product managers, and stakeholders to align model development with business goals. Communicate technical insights clearly to both technical and non-technical stakeholders. 5. Model Deployment and Monitoring Deploy models to production using MLOps practices and tools (e.g., MLflow, Docker, Kubernetes). Monitor live model performance, diagnose issues, and implement improvements as needed. 6. Staying Current with AI/ML Advancements Stay informed of current research, tools, and trends in AI and machine learning. Evaluate and recommend emerging technologies to maintain innovation within the team. 7. Code Reviews and Best Practices Participate in code reviews to ensure code quality, scalability, and adherence to best practices. Promote knowledge sharing and mentoring within the development team. Required Skills and Qualifications: Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field. 4-5 years' of experience in machine learning, artificial intelligence, or applied data science roles. Strong programming skills in Python (preferred) and/or R. Proficiency in ML libraries and frameworks , including: scikit-learn, XGBoost, LightGBM, TensorFlow or Keras, PyTorch Skilled in data preprocessing and feature engineering , using; pandas, numpy, sklearn.preprocessing Practical experience in deploying ML models into production environments using REST APIs and containers. Familiarity with version control systems (e.g., Git) and containerization tools (e.g., Docker). Experience working with cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure . Understanding software development methodologies , especially Agile/Scrum. Strong analytical thinking, debugging, and problem-solving skills in real-world AI/ML applications.

Job Description Design and develop machine learning models tailored to mechanical engineering challenges, including predictive modelling, simulation optimisation, and failure analysis. Utilise deep learning and other advanced ML techniques to improve the accuracy and efficiency of CAE simulations. Preprocess and analyse large datasets from CAE simulations, experimental tests, and manufacturing processes for modelling. Train, validate, and fine-tune machine learning models using real-world engineering data. Optimise models for performance, scalability, and robustness in production environments. Collaborate with CAE engineers to integrate ML models into existing simulation workflows (e.g., FEA, CFD, structural analysis). Automate repetitive simulation tasks and enable predictive analytics for design optimisation. Work closely with mechanical engineers, data scientists, and software developers to identify business challenges and develop data-driven solutions. Deploy machine learning models into production environments and monitor their performance. Maintain and update models to ensure reliability and continuous improvement. Stay abreast of the latest advancements in machine learning, AI, and CAE technologies. Apply innovative approaches to solve complex engineering problems. Requirements Bachelors or Master’s degree in Mechanical Engineering, Computer Science, or a related field Proven 2-3 years of experience in developing and deploying machine learning models, preferably in mechanical engineering or CAE domain Hands-on experience with CAE tools such as ANSYS, Abaqus, or similar FEA/CFD software Strong programming skills in Python, R, or Java Proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience with data preprocessing, feature engineering, and statistical analysis Solid understanding of mathematics, statistics, and problem-solving skills Excellent analytical thinking and ability to tackle complex engineering challenges Strong communication and teamwork skills to collaborate across disciplines Preferred: Experience with physics-informed machine learning and digital twin technologies Preferred: Familiarity with automation of CAE workflows and predictive modelling for product design Benefits Challenging job and a chance to team up with a young and dynamic professional group Chance to build yourself as WE grow. Remuneration that stays competitive and attractive to retain the best. Opportunity to join an organization experiencing year on year growth.

AI / Machine Learning / Data Science part time Work from Home (Any where in world) Warm Greetings from Excel Online Classes, We are a team of industry professionals running an institute that provides comprehensive online IT training, technical support, and development services. We are currently seeking AI / Machine Learning / Data Science Experts who are passionate about technology and can collaborate with us in their free time. If you're enthusiastic, committed, and ready to share your expertise, we would love to work with you! Were hiring for the following services: Online Training Online Development Online Technical Support Conducting Online Interviews Corporate Training Proof of Concept (POC) Projects Research & Development (R&D) We are looking for immediate joiners who can contribute in any of the above areas. If you're interested, please fill out the form using the link below: https://docs.google.com/forms/d/e/1FAIpQLSdvut0tujgMbBIQSc6M7qldtcjv8oL1ob5lBc2AlJNRAgD3Cw/viewform We also welcome referrals! If you know someone—friends, colleagues, or connections—who might be interested in: Teaching, developing, or providing tech support online Sharing domain knowledge (e.g., Banking, Insurance, etc.) Teaching foreign languages (e.g., Spanish, German, etc.) Learning or brushing up on technologies to clear interviews quickly Upskilling in new tools or frameworks for career growth Please feel free to forward this opportunity to them. For any queries, feel free to contact us at: excel.onlineclasses@gmail.com Thank you & Best Regards, Team Excel Online Classes excel.onlineclasses@gmail.com

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

Strong expertise in deploying machine learning models in real-world environments. Hands-on experience in Automated Valuation Models (AVM) , LangChain , and LLM-powered applications . Proficiency with Python-based data science tools like Pandas , NumPy , Scikit-learn , XGBoost , and LightGBM . Skilled in feature engineering , data intelligence extraction , and handling structured, semi-structured, and unstructured data . Experience integrating models into APIs and production environments.

Job Title: Data/ML Platform Engineer Location: Gurgaon, Pune, Bangalore, Chennai, Bhopal, Jaipur, Hyderabad (Work from office) Notice Period: ImmediateiSource Services is hiring for one of their client for the position of Data/ML Platform Engineer. As a Data Engineer you will be relied on to independently develop and deliver high-quality features for our new ML Platform, refactor and translate our data products and finish various tasks to a high standard. Youll be part of the Data Foundation Team, which focuses on creating and maintaining the Data Platform for Marktplaats. 5 years of hands-on experience in using Python, Spark,Sql. Experienced in AWS Cloud usage and management. Experience with Databricks (Lakehouse, ML, Unity Catalog, MLflow). Experience using various ML models and frameworks such as XGBoost, Lightgbm, Torch. Experience with orchestrators such as Airflow and Kubeflow. Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes). Fundamental understanding of Parquet, Delta Lake and other data file formats. Proficiency on an IaC tool such as Terraform, CDK or CloudFormation. Strong written and verbal English communication skill and proficient in communication with non-technical stakeholderst Location - Gurgaon, Pune, Bangalore, Chennai, Bhopal, Jaipur, Hyderabad (Work from office)

AI/ML Models: Experience with Automated Valuation Models (AVM) and real-world deployment of machine learning models LangChain: Proficient in using LangChain for building LLM-powered applications Data Science Toolkit: Hands-on with Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, and Jupyter Feature Engineering: Strong background in feature engineering and data intelligence extraction Data Handling: Comfortable with structured, semi-structured, and unstructured data Production Integration: Experience integrating models into APIs and production environments using Python-based frameworks Location-Remote, Delhi NCR, Bangalore, Chennai, Pune, Kolkata, Ahmedabad, Mumbai, Hyderabad

Job Summary: We are looking for a highly skilled and experienced AI/ML Developer with 3-4 years of hands-on experience to join our technology team. You will be responsible for designing, developing, and optimizing machine learning models that drive intelligent business solutions. The role involves close collaboration with cross-functional teams to deploy scalable AI systems and stay abreast of evolving trends in artificial intelligence and machine learning. Key Responsibilities: 1. Develop and Implement AI/ML Models Design, build, and implement AI/ML models tailored to solve specific business challenges, including but not limited to natural language processing (NLP), image recognition, recommendation systems, and predictive analytics. 2. Model Optimisation and Evaluation Continuously improve existing models for performance, accuracy, and scalability. 3. Data Preprocessing and Feature Engineering Collect, clean, and preprocess structured and unstructured data from various sources. Engineer relevant features to improve model performance and interpret ability. 4. Collaboration and Communication Collaborate closely with data scientists, back end engineers, product managers, and stakeholders to align model development with business goals. Communicate technical insights clearly to both technical and non-technical stakeholders. 5. Model Deployment and Monitoring Deploy models to production using MLOps practices and tools (e.g., MLflow, Docker, Kubernetes). Monitor live model performance, diagnose issues, and implement improvements as needed. 6. Staying Current with AI/ML Advancements Stay informed of current research, tools, and trends in AI and machine learning. Evaluate and recommend emerging technologies to maintain innovation within the team. 7. Code Reviews and Best Practices Participate in code reviews to ensure code quality, scalability, and adherence to best practices. Promote knowledge sharing and mentoring within the development team. Required Skills and Qualifications: Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field. 3-4 years of experience in machine learning, artificial intelligence, or applied data science roles. Strong programming skills in Python (preferred) and/or R. Proficiency in ML libraries and frameworks , including: scikit-learn, XGBoost, LightGBM, TensorFlow or Keras, PyTorch Skilled in data preprocessing and feature engineering , using; pandas, numpy, sklearn.preprocessing Practical experience in deploying ML models into production environments using REST APIs and containers. Familiarity with version control systems (e.g., Git) and containerization tools (e.g., Docker). Experience working with cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure . Understanding software development methodologies , especially Agile/Scrum. Strong analytical thinking, debugging, and problem-solving skills in real-world AI/ML applications.

Key Responsibilities: Collaborate with data scientists to support end-to-end ML model development, including data preparation, feature engineering, training, and evaluation. Build and maintain automated pipelines for data ingestion, transformation, and model scoring using Python and SQL.. Assist in model deployment using CI/CD pipelines (e.g., Jenkins) and ensure smooth integration with production systems. Develop tools and scripts to support model monitoring, logging, and retraining workflows. Work with data from relational databases (RDS, Redshift) and preprocess it for model consumption. Analyze pipeline performance and model behavior; identify opportunities for optimization and refactoring. Contribute to the development of a feature store and standardized processes to support reproducible data science. Required Skills & Experience: 13 years of hands-on experience in Python programming for data science or ML engineering tasks. Solid understanding of machine learning workflows, including model training, validation, deployment, and monitoring. Proficient in SQL and working with structured data from sources like Redshift, RDS, etc. Familiarity with ETL pipelines and data transformation best practices. Basic understanding of ML model deployment strategies and CI/CD tools like Jenkins. Strong analytical mindset with the ability to interpret and debug data/model issues. Preferred Qualifications: Exposure to frameworks like scikit-learn, XGBoost, LightGBM, or similar. Knowledge of ML lifecycle tools (e.g., MLflow, Ray). Familiarity with cloud platforms (AWS preferred) and scalable infrastructure. Experience with data or model versioning tools and feature engineering frameworks.

Role & responsibilities We are seeking an experienced and technically strong Machine Learning Engineer to design, implement, and operationalize ML models across Google Cloud Platform (GCP) and Microsoft Azure. The ideal candidate will have a robust foundation in machine learning algorithms, MLOps practices, and experience deploying models into scalable cloud environments. Responsibilities: Design, develop, and deploy machine learning solutions for use cases in prediction, classification, recommendation, NLP, and time series forecasting. Translate data science prototypes into production-grade, scalable models and pipelines. Implement and manage end-to-end ML pipelines using: Azure ML (Designer, SDK, Pipelines), Data Factory, and Azure Databricks Vertex AI (Pipelines, Workbench), BigQuery ML, and Dataflow Build and maintain robust MLOps workflows for versioning, retraining, monitoring, and CI/CD using tools like MLflow, Azure DevOps, and GCP Cloud Build. Optimize model performance and inference using techniques like hyperparameter tuning, feature selection, model ensembling, and model distillation. Use and maintain model registries, feature stores, and ensure reproducibility and governance. Collaborate with cloud architects, and software engineers to deliver ML-based solutions. Maintain and monitor model performance in production using Azure Monitor, Prometheus, Vertex AI Model Monitoring, etc. Document ML workflows, APIs, and system design for reusability and scalability. Primary Skills required (Must Have Expereince): 5 -7 years of experience in machine learning engineering or applied ML roles. Advanced proficiency in Python, with strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. Solid understanding of core ML concepts: supervised/unsupervised learning, cross-validation, bias-variance tradeoff, evaluation metrics (ROC-AUC, F1, MSE, etc.). Hands-on experience deploying ML models using: Azure ML (Endpoints, SDK), AKS, ACI Vertex AI (Endpoints, Workbench), Cloud Run, GKE Familiarity with cloud-native tools for storage, compute, and orchestration: Azure Blob Storage, ADLS Gen2, Azure Functions GCP Storage, BigQuery, Cloud Functions Experience with containerization and orchestration (Docker, Kubernetes, Helm). Strong understanding of CI/CD for ML, model testing, reproducibility, and rollback strategies. Experience implementing drift detection, model explainability (SHAP, LIME), and responsible AI practices.