1435 Deep Learning Jobs - Page 17

Conducting classroom Training on programming skills Creating a positive and engaging learning environment A passion for teaching and helping students achieve their career goals Strong knowledge of SQL. Python, Data Science, ML, DL, NLP, Power Bi

What you get to do in this role: Generate and evaluate synthetic data tailored to improve the robustness, performance, and safety of machine learning models, particularly large language models (LLMs). Train and fine-tune models using curated datasets, optimizing for performance, reliability, and scalability. Design and implement evaluation metrics to rigorously measure and monitor model quality, safety, and effectiveness. Conduct experiments to validate model behavior and improve generalization across diverse use cases. Collaborate with engineering and research teams to identify risks and recommend AI safety mitigation strategies. Participate in the development, deployment, and continuous improvement of end-to-end AI solutions. Contribute to architectural and technology decisions related to AI infrastructure, frameworks, and tooling. Promote modern engineering practices including continuous integration, continuous delivery, and containerized workflows. Key qualifications: 5+ years of experience in machine learning, deep learning, and AI systems. Proficiency in Python and frameworks like PyTorch, TensorFlow, and NumPy. Experience in synth

We are seeking a skilled and experienced Machine Learning Engineer specialized in Natural Language Processing (NLP) and Computer Vision to join our team. The candidate should have a strong foundation in ML and AI principles, coupled with a proven track record of developing and deploying a minimum of 20+ models in these domains. Responsibilities: Develop and implement state-of-the-art machine learning algorithms and models for NLP and computer vision applications. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Conduct thorough data analysis, pre-processing, and feature engineering to extract meaningful insights from structured and unstructured data. Design and implement scalable and efficient machine learning pipelines for training, evaluation, and inference. Experiment with various deep learning architectures, hyper parameters, and optimization techniques to improve model performance. Stay updated with the latest advancements in ML and AI research and evaluate their potential applications in our domain. Work closely with software engineers to integrate ML models into production systems and ensure their robustness and scalability. Perform rigorous testing and validation of models to ensure their accuracy, reliability, and generalization capability. Continuously monitor and maintain deployed models, and implement necessary updates and enhancements as required. Document code, methodologies, and findings effectively, and contribute to internal knowledge sharing initiatives. Bachelor's/Masters/Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field. Strong theoretical understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques. Proficiency in programming languages such as Python, along with experience in popular ML libraries such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience in developing and deploying machine learning models for NLP and computer vision tasks, with a demonstrable portfolio of projects. Solid understanding of natural language processing techniques, including text classification, sentiment analysis, named entity recognition, etc. Familiarity with computer vision concepts such as image classification, object detection, image segmentation, etc., and experience with frameworks like OpenCV or TensorFlow. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Excellent problem-solving skills, attention to detail, and ability to work independently as well as part of a team. Strong communication and interpersonal skills, with the ability to effectively collaborate with stakeholders across different functional areas. We need only Data Scientist Candidates. For More Information Kindly call on 7701968943(Sanchit) Share your updated cv on sanchit@mounttalent.com

Summary: As an AI/ML Engineer, you will be developing applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. You will apply GenAI models as part of the solution, including deep learning, neural networks, chatbots, and image processing. Professional & Technical Skills: - Must To Have Skills: Proficiency in Natural Language Processing (NLP). - Strong understanding of statistical analysis and machine learning algorithms. For NLP-Must have- NLP, Gen AI, ML, AI & DS-5+ yrs exp.

Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. 6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. Familiarity with vector databases and embedding techniques. Experience deploying models using APIs, Docker, and cloud platforms Strong analytical, problem-solving, and communication skills. Experience in ML Ops, Model deployment, Model lifecycle and management

Voicecare AI is a Healthcare Administration General Intelligence (HAGI) company for the back-office and the RCM industry. We are building a safety focused large and small conversational language model for the healthcare industry. Our mission is to dramatically improve access, adherence, and outcomes for the patients and the healthcare workforce through the application of generative AI. We are a venture-backed company partnering with the top healthcare stakeholders in the country. We are seeking a Machine Learning NLP Engineer to drive the development of large language models (LLMs), deep learning architectures, and speech processing systems. This role is critical for AI-driven healthcare solutions while ensuring high performance, accuracy, and compliance with healthcare standards. Responsibilities: Machine Learning Deep Learning Development Design and implement machine learning algorithms for healthcare AI applications. Build and optimize deep learning models to enhance AI-driven decision-making processes. LLM Fine-Tuning Training Develop and fine-tune and train large and small language models to meet domain-specific requirements. Design robust data preparation and training pipelines for efficient model performance. LLM Architecture Expertise Work with state-of-the-art LLM architectures such as Transformers, GPT models, LLaMA, and others Research and implement novel enhancements to existing language models for better contextual understanding. Speech NLP Project Execution Implement speech-to-text and text-to-speech models for healthcare applications. Develop NLP solutions for intent prediction, sentiment analysis, and medical language translation. Programming Development Write and maintain high-performance Python code for ML/NLP applications. Utilize frameworks like PyTorch and TensorFlow to train and deploy AI models. Additional Contributions (Optional but Preferred) Apply advanced prompt engineering techniques for optimizing LLM interactions. Deploy ML models on cloud platforms (AWS, GCP, Azure) for scalability. Implement MLOps best practices, including CI/CD pipelines for ML and model monitoring. Skills and Experience: Machine Learning Deep Learning: Strong experience in designing, training, and deploying ML/DL models. LLM Expertise: Hands-on experience in fine-tuning and optimizing LLMs. NLP Speech Processing: Experience in developing NLP solutions and speech models. Programming: Advanced Python skills with proficiency in PyTorch and TensorFlow. LLM Architecture: Deep Knowledge of modern transformer-based models. MLOps Cloud: Demonstrated experience with cloud deployment, CI/CD for ML, and model monitoring. Qualifications: Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3+ years of experience in ML, NLP, or AI-driven model development. Proven track record of deploying LLM-based solutions in real-world applications. Experience working in healthcare AI, health tech startups, or regulated industries is a plus. Relevant certifications preferred (e.g., Google Professional ML Engineer, AWS Certified Machine Learning - Specialty). Candidates located in Bangalore is a plus Candidates from top universities is a plus

Academics Manager- Data Science: About the Role: As an Academic Manager for the Data Science program at Newton School, you will lead the end-to-end academic experience driving curriculum delivery, student engagement, and mentor coordination. This role demands a strong grasp of data analytics and program management, high collaboration with cross-functional teams, and direct exposure to leadership, sales, and partnerships. If youre passionate about transforming education through innovative teaching strategies and hands-on learning, this is the role for you. Key Responsibilities Collaborate with cross-functional teams to serve as an Academic Manager, ensuring alignment with students learning goals and pedagogical intent. Deliver an engaging teaching experience from foundational concepts to practical application and ultimately, outcome-oriented education across diverse student groups and courses. Establish processes and implement innovative strategies for creating and utilizing technical content tailored for various stakeholders, including students, instructors, mentors, and teaching assistants. Handle the end-to-end experience for Data Science program at Newton School, from learning to mentor alignment to outcome. High face time with leadership team along with sales marketing partnerships Bonus Points / Preferred Qualifications Prior experience in a similar role at an ed-tech company or academic institution Mandatory good knowledge of data analytics stacks and program management. Demonstrated passion for revolutionising teaching methodologies and rethinking traditional education frameworks. Academics Manager- Data Science: About the Role: ...

Locations : Hyderabad, Telangana, India Role ID 209546 Worker Type Regular Employee Studio/Department CTO - EA Digital Platform Work Model Hybrid Description Requirements Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen. Software Engineer II - AI/ML Engineer The EA Digital Platform (EADP) group is the core powering the global EA ecosystem. We provide the foundation for all of EA s incredible games and player experiences with high-level platforms like Cloud, Commerce, Data and AI, Gameplay Services, Identity and Social. By providing reusable capabilities that game teams can easily integrate into their work, we let them focus on making some of the best games in the world and creating meaningful relationships with our players. We re behind the curtain, making it all work together. Come power the future of play with us. The Challenge Ahead: We are looking for developers who want to work on a large-scale distributed data system that empowers EA Games to personalize player experience and engagement. Responsibilities You will help with designing, implementing and optimizing the infrastructure for AI model training and deployment platform You will help with integrating AI capabilities into existing software systems and applications You will develop tools and systems to monitor the performance of the platform in real-time, analyzing key metrics, and proactively identify and address any issues or opportunities for improvement. You will participate in code reviews to maintain code quality and ensure best practices You will help with feature and operation enhancement for platform under senior guidance You will help with improving the stability and observability of the platform Qualifications Bachelors degree or foreign degree equivalent in Computer Science, Electrical Engineering, or related field. 3+ years of experience with software development and model development Experience with a programming language such as Go, Java or Scala Experience with scripting languages such as bash, awk, python Experience with Scikit-Learn, Pandas, Matplotlib 3+ years of experience with Deep Learning frameworks like PyTorch, TensorFlow, CUDA Hands-on experience of any ML Platform (Sagemaker, Azure ML, GCP Vertex AI) Experience with cloud services and modern data technologies Experience with data streaming and processing systems About Electronic Arts We re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth. We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do. Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law. LinkedInID 1449 Back to Role List

Job Title: Data Scientist Location: Chennai Experience: 4-8 Years Skills Required: 4 + years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering /classification/ decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms. Looking for qualified Data Scientists who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, and Optimization. Potential candidates should have hands-on experience in applying first principles methods, machine learning, data mining, and text mining techniques to build analytics prototypes that work on massive datasets. Candidates should have experience in manipulating both structured and unstructured data in various formats, sizes, and storage-mechanisms. Candidates should have excellent problem-solving skills with an inquisitive mind to challenge existing practices. Candidates should have exposure to multiple programming languages and analytical tools and be flexible to using the requisite tools/languages for the problem at-hand.

Overview Provide data science / analytics support for the Perfect Store group who works with AMESA Sectors, a part of the broader Global Capability Center in Hyderabad, India. This role will help to enable accelerated growth for PepsiCo by building Retailer Value Offer and Shopper Value offer, aligning data, and performing advance analytics approaches for PepsiCo to drive actionable insights at Business Unit, store level. Key responsibilities will be to build and manage advance analytics-deep dives in a cloud environment, manage data and prepare data to be used for advanced analytics, artificial intelligence, machine learning, and deep learning projects. Responsibilities Support Perfect Store (Demand Accelerator) team with delivery of Retail Value Offer, Shopper Value Offer framework for AMESA sector Work within cloud environment (e.g., Microsoft Azure) Build and maintain codes for use in advanced analytics, artificial intelligence, and machine learning projects Clean and prepare data for use in advanced analytics, artificial intelligence, and machine learning projects Build deep dive analysis reports in cloud environment (using Pyspark and Python) to support BU Ask Develop, maintain, and apply statistical techniques to business questions - including Distribution, Outliers, visualizations etc. Support relationships with the key end-user stakeholders with Business Units-AMESA Own flawless execution AND Quality Check of analytics exercises Responsible for managing multiple priorities; being able to manage deadlines and deliverables Lead communication with Business Partners and potentially end-users on matters such as available capacity, changes of scope of existing projects and planning of future projects Deliver outputs in line with the agreed timelines and formats while updating existing project management tools Flag and monitor any business risks related to delivering the requested outputs Qualifications An experienced analytics profession with 4 years+ experience EducationB.Tech or any bachelors degree. Masters are optional Proficient with Python, SQL, Excel and PowerBI Plus, to have knowledge on Machine Learning algorithms Good to have Retail experience Strong collaboratorInterested and motivated by working with others. Owns the full responsibility of deliverables, quality check thoroughly, look for and work on improvements in the process Actively creates and participates in opportunities to co-create solutions across markets. Willing and able to embrace Responsive Ways of Working

Responsibilities : The responsibilities include teaching a requisite number of classes, providing guidance and supervision to graduate students, participating in departmental meetings, and providing academic support to Professors and other faculty members. You should be able to pace your lessons. Assisting with various departmental duties and providing academic support to Professors and other staff. Teaching and supervising undergraduate and graduate students. Providing demonstrations and supervising experiments and investigations. Answering questions in class or via email or telephone. Providing Professors and Department Heads with feedback on student progress. Attending faculty and departmental meetings and voicing concerns or providing suggestions for improvement.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

We're seeking an experienced AI/ML Engineer who thrives on curiosity and innovation to join our dynamic engineering team. This role offers an exciting chance to tackle impactful real-world machine learning challenges and play a key part in developing advanced, state-of-the-art AI solutions. Role & responsibilities Architect, train, fine-tune, and distill LLMs and deep-learning models for NLP, generative AI, and agentic AI applications. Assist in designing, developing, and training machine learning models using structured and unstructured data Conduct thorough testing, evaluation, benchmarking, and validation to ensure performance and robustness Deploy models into production using MLOps pipelines (CI/CD, versioning, monitoring) Optimize models and inference pipelines for latency, throughput, and compute efficiency Mentor junior engineers and collaborate cross-functionally with data engineers, DevOps, product managers Curate, cleanse, and transform extensive datasets to prepare them for robust model development. Conduct insightful exploratory data analysis and apply advanced statistical modeling techniques. Execute systematic experiments, optimize hyperparameters, and rigorously assess models using established performance metrics. Maintain comprehensive documentation detailing model architectures, data pipelines, and experimental outcomes. Develop and integrate AI-enhanced tools including web-search functionalities, intelligent image editing, and related applications. Support in integrating AI/ML models into production environments Skill Sets We Require- Frameworks: PyTorch (latest, including TorchDynamo), TensorFlow 2.x Finetuning & Distillation: Implement teacherstudent training, supervised finetuning, responsebased distillation and Transorfermers. Model Lifecycle Hands-on experience with Python and ML libraries such as scikit-learn, pandas, NumPy. Understanding of probability, statistics, and linear algebra APIs & Storage: RESTful APIs, ONNX, SQL/NoSQL databases, S3 Buckets. CI/CD: Git, GitHub Actions, Docker Registry, automated testing & deployment (Good to have) Required Qualifications- Btech/BE in Computer Science or Equivalent Field 4+ years of hands-on experience in training, tuning, and deploying LLMs and deep-learning models. Proficient with PyTorch, Transformer frameworks

Responsibilities: Develop machine learning models using Python & PyTorch. Optimize data architecture for efficiency & accuracy. Collaborate with cross-functional teams on AI projects.

So, what’s the role all about? We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate should have a minimum 4s of years of experience in data science, with hands-on experience in developing and implementing Generative AI solutions. The Senior Data Scientist will be responsible for developing Machine Learning models and collaborating with cross-functional teams to solve complex business problems How will you make an impact? Develop and execute advanced analytics projects from end to end, including data collection, preprocessing, model development, evaluation, and deployment. Develop predictive models and machine learning algorithms to extract actionable insights from large and complex datasets. Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data. Collaborate with stakeholders to understand business requirements and translate them into analytical solutions that drive value and impact. Stay abreast of the latest advancements in Data Science, Machine Learning, Generative AI and recommend innovative approaches to solve business challenges Have you got what it takes? Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; advanced degree (Master's or Ph.D.) preferred. Minimum of 4 years of hands-on experience in data science and machine learning , with at least 6 months of experience in Generative AI development. Proficiency in programming languages such as Python or R, as well as experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, Hugging Face - Transformers, LangChain etc.). Strong understanding of machine learning techniques and algorithms, including supervised and unsupervised learning, regression, classification, clustering, and deep learning. Strong understanding of LLMs, NLP techniques, and evaluation methods for generative outputs. Solid foundation in prompt engineering for optimizing AI-generated outputs across different tasks and domains. Excellent problem-solving skills and ability to work independently as well as collaboratively in a fast-paced environment. Strong communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences. Proven leadership abilities, with experience in mentoring junior team members and leading cross-functional projects. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Preferred Qualifications: Experience working in industries such as finance, banking. Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services for building and deploying machine learning models. Knowledge of data visualization tools (e.g., Tableau, Power BI) for creating interactive dashboards and reports. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Hands-on experience with vector databases (e.g. Pinecone) and embedding techniques. What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7409 Reporting into: Tech Manager Role Type: Individual Contributor

5+yrs experience Proficiency in ML frameworks (e.g., TensorFlow, Py Torch). Experience with natural language processing (NLP) and large language models (LLMs). Understanding of generative models and their applications. Proficiency in programming languages such as Python, Go, or Java. Experience in developing APIs and integrating AI models into existing systems. Familiarity with containerization tools (e.g., Docker, Kubernetes). Experience with (CI/CD) pipelines and databases or data lakes, and/or real-time data processing frameworks.

Artificial Intelligence and Machine Learning Engineering – Associate Director, Corporate Technology

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Looking for experienced Data Scientist Candidates. Job Description Leveraging knowledge in analytical and statistical algorithms to assist stakeholders in improving their business Partnering on the design and implementation of statistical data quality procedures for existing and new data sources Communicating complex data science solutions, concepts, and analyses to team members and business leaders Presenting data insights & recommendations to key stakeholders Establishing links across existing data sources and finding new, interesting data correlations Ensuring testing and validation are components of all analytics solutions Skills : Strong proficiency in predictive analytics, prescriptive analytics, AI, machine learning, and statistical modeling Proficiency in programming languages such as Python and SQL for data analysis and model development. Working with text data including Natural Language Processing (NLP) techniques such as tokenization, lemmatization, sentiment analysis, text classification, topic modeling, and entity recognition Hands-on experience with advanced AI techniques such as Retrieval-Augmented Generation (RAG), vector databases, and LLM integration for enhanced information retrieval and generation, GPT, and BERT Strong understanding of Machine Learning concepts including supervised and unsupervised learning, model training, evaluation, and deployment

**Key Responsibilities** People management - Lead a team of software engineers, DS, DE, MLE, in the design, development, and delivery of software solutions. Program management - Strong program leader that has run program management functions to efficiently deliver ML projects to production and manage its operations. Work with Business stakeholders & customers in the Retail Business domain to execute the product vision using the power of AI/ML. Scope out the business requirements by performing necessary data-driven statistical analysis. Set goals and, objectives using proper business metrics and constraints. Conduct exploratory analysis on large volumes of data, understand the statistical shape, and use the right visuals to drive & present the analysis. Analyse and extract relevant information from large amounts of data and derive useful insights on a big-data scale. Create labelling manuals and work with labellers to manage ground truth data and perform feature engineering as needed. Work with software engineering teams, data engineers and ML operations team (Data Labellers, Auditors) to deliver production systems with your deep learning models. Select the right model, train, validate, test, optimise neural net models and keep improving our image and text processing models. Architecturally optimize the deep learning models for efficient inference, reduce latency, improve throughput, reduce memory footprint without sacrificing model accuracy. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. Create and enhance model monitoring system that could measure data distribution shifts, alert when model performance degrades in production. Streamline ML operations by envisioning human in the loop kind of workflows, collect necessary labels/audit information from these workflows/processes, that can feed into improved training and algorithm development process. Maintain multiple versions of the model and ensure the controlled release of models. Manage and mentor junior data scientists, providing guidance on best practices in data science methodologies and project execution. Lead cross-functional teams in the delivery of data-driven projects, ensuring alignment with business goals and timelines. Collaborate with stakeholders to define project objectives, deliverables, and timelines. **Skills required: ** MS/PhD from reputed institution with a delivery focus. 5+ years of experience in data science, with a proven track record of delivering impactful data-driven solutions. Delivered AI/ML products/features to production. Seen the complete cycle from Scoping & analysis, Data Ops, Modelling, MLOps, Post deployment analysis. Experts in Supervised and Semi-Supervised learning techniques. Hands-on in ML Frameworks - Pytorch or TensorFlow. Hands-on in Deep learning models. Developed and fine-tuned Transformer based models. ( Input output metric, Sampling technique) Deep understanding of Transformers, GNN models and its related math & internals. Exhibit high coding standards and create production quality code with maximum efficiency. Hands-on in Data analysis & Data engineering skills involving Sqls, PySpark etc. Exposure to ML & Data services on the cloud AWS, Azure, GCP Understanding internals of compute hardware - CPU, GPU, TPU is a plus. Can leverage the power of hardware accel to optimize the model execution — PyTorch Glow, cuDNN, is a plus.

Role & responsibilities Design, prepare and deliver lectures and hands-on training sessions on: Python programming Machine Learning Data Analytics Deep Learning Statistics and Probability Tools like NumPy, Pandas, Scikit-learn, Matplotlib, Jupyter, etc. Develop and update curriculum, course content, and learning materials. Conduct assessments, evaluate student performance, and provide constructive feedback. Mentor students on academic and project work. Stay current with the latest developments in the field and incorporate new tools and technologies. Conduct workshops, seminars, and guest lectures to enhance learning outcomes. Collaborate with academic and administrative teams to ensure effective course delivery. Required skills: Bachelor's/Masters degree Strong proficiency in Python and data analysis libraries. Hands-on experience with machine learning algorithms and frameworks. Good understanding of statistical techniques and data visualization. Prior teaching/training experience preferred. Excellent communication and presentation skills. Ability to simplify complex topics for beginner to advanced learners.