23 Mxnet Jobs

You have over 5 years of experience in building production-grade Neural Network models using Computer Vision or Natural Language Processing techniques. You possess a strong understanding of various machine learning techniques and algorithms, including k-NN, Naive Bayes, SVM, Decision Forests, and Neural Networks. Experience with Deep Learning frameworks like TensorFlow, PyTorch, and MxNet is part of your skillset. Proficiency in common data science toolkits such as R, Sklearn, NumPy, MatLab, and MLib is highly desirable. Additionally, you have solid applied statistics skills encompassing distributions, statistical testing, and regression. Your expertise extends to using query languages like SQL, Hive, Pig, and NoSQL databases. In this role, you will collaborate with Product Managers, Architects, and Engineering Leadership to conceptualize, strategize, and develop new products focused on AI/ML initiatives. You will be responsible for developing, driving, and executing the long-term vision and strategy for the Data Science team by engaging with multiple teams and stakeholders across the organization. Your tasks will involve architecting, designing, and implementing large-scale machine learning systems. Specifically, you will develop Neural Network models for information extraction from mortgage documents using Computer Vision and NLP techniques. Ad-hoc analysis and clear presentation of results to various audiences and key stakeholders will be part of your routine. You will also design experiments, test hypotheses, and build models while conducting advanced data analysis and highly complex algorithm designs. Applying advanced statistical, predictive, and machine learning modeling techniques to enhance multiple real-time decision systems will be a key aspect of your role. You will collaborate with development teams to deploy models in the production environment to support ML-driven product features. Furthermore, you will define business-specific performance metrics to assess model effectiveness and continuously monitor and enhance these metrics over time for models in a production environment. To qualify for this position, you should hold an M.S. in mathematics, statistics, computer science, or a related field, with a Ph.D. degree being preferred. You must have over 5 years of relevant quantitative and qualitative research and analytics experience. Excellent communication skills and the ability to effectively convey complex topics to a diverse audience are essential attributes for this role.,

Oliver Wyman is a global leader in management consulting with offices in 70 cities across 30 countries. Combining deep industry knowledge with specialized expertise in strategy, finance, operations, technology, risk management, and organizational transformation, our team of 6000+ professionals helps clients optimize their business, improve IT, operations, and risk profile, and accelerate organizational performance. We challenge conventional thinking, consistently deliver innovative solutions, and have a tangible impact on clients" top and bottom lines. Our clients are the CEOs and executive teams of the top global 1000 companies. Oliver Wyman is a business of Marsh McLennan [NYSE: MMC]. At Oliver Wyman DNA in Gurugram, India, we partner with clients to solve tough strategic business challenges using analytics, technology, and industry expertise. Our goal is to achieve lasting results in collaboration with clients and stakeholders, driving digital transformation, creating customer-focused solutions, and optimizing operations for the future. We value personal and professional growth opportunities and aim to deliver impact globally as an entrepreneurial team. Our mission is to leverage India's high-quality talent to provide exceptional analytics-driven management consulting services that empower clients globally. By working alongside Oliver Wyman consulting teams, we aim to achieve sustainable growth and drive meaningful impact for our global client base. Our purpose is to bring together a diverse team of highest-quality talent equipped with innovative analytical tools to build long-lasting partnerships with clients based on trust, mutual respect, and a commitment to deliver results. We have open positions ranging from Associate Data Scientist to Director, providing talented professionals with excellent career and growth opportunities. We seek individuals with relevant experience in quantitatively intense areas to join our team. In the data scientist track, you will be responsible for managing and delivering analytics projects, designing analytics solutions, crafting models, and driving scalable high-quality solutions across industries. Your responsibilities include working with global clients, exploring large-scale data, shaping proposals, refining model insights, leading the development of statistical techniques and ML algorithms, and staying updated on emerging data science techniques. To be successful in this role, you should have a Bachelor's or Master's degree in a quantitative discipline, prior experience in data science and analytics, a passion for problem-solving through big data, impactful presentation skills, excellent communication skills, willingness to travel, and proficiency in modern programming languages and machine learning frameworks. You should also have a solid foundational knowledge of mathematical and statistical principles, familiarity with cloud storage and computational frameworks, and a collaborative team player mindset with respect for confidentiality. The interview process will include testing technical proficiency, case study, and team-fit interviews. If you are interested in joining our team, please include a brief note introducing yourself, what you're looking for in the role, and your potential value-add to our team. We are hiring for data and analytics roles across the levels from Associate Data Scientist to Director level for experience ranging from 0-15 years. In addition to the base salary, this position may be eligible for performance-based incentives, and we offer a competitive total rewards package including comprehensive health and welfare benefits.,

As an experienced machine learning professional with expertise in deep learning and statistical modeling for earth observation data applications, your key responsibilities will include developing models for segmentation, object classification, crop monitoring, and disaster management. It is essential for you to have proficiency in Python, ML frameworks such as TensorFlow and PyTorch, and strong research skills. An advanced degree is required for this role. SatSure is a deep tech, decision intelligence company that focuses on agriculture, infrastructure, and climate action in the developing world. The company aims to make insights from earth observation data accessible to all. Joining SatSure means being at the forefront of building a deep tech company from India that aims to solve global problems. In this role, you will be responsible for implementing deep-learning models and frameworks for various applications in agriculture and infrastructure using earth observation data. You will design and implement performance evaluation frameworks, explore new methods for improving performance, and build model monitoring and active learning pipelines. Additionally, you will work on solving research problems related to land use and land cover (LULC), crop classification, change monitoring, and disaster management using earth observations. To qualify for this role, you should have a master's degree or PhD in Engineering, Statistics, Mathematics, or Computer Science with 5-8 years of experience in machine learning-based data product research and development. Proficiency in tools and frameworks related to computer science, probability, statistics, learning theory, and deep learning fundamentals is required. Experience with statistical modeling techniques and deep learning models like CNN, RNN, Transformers, and GANs is necessary. You should also be proficient in Python and have hands-on experience in using ML frameworks such as TensorFlow, PyTorch, PyTorch Lightning, and MxNet. Additional qualifications include the ability to design, develop, and optimize machine learning/deep learning models, knowledge of applying ML to earth observation data, and an appetite for research and implementing innovative solutions for complex problems. In addition to a challenging and rewarding work environment, SatSure offers benefits such as medical health cover for you and your family, access to mental health experts, dedicated allowances for learning and skill development, and a comprehensive leave policy. The interview process includes an introductory call, assessment, presentation, multiple interview rounds, and a culture/HR round. Join SatSure to be a part of a dynamic team that is making a positive impact on the world through innovative technology and deep learning solutions.,

The Senior Data Science Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. Key Responsibilities: 1. Architecting & Scaling Agentic AI Solutions: - Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. - Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. - Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization: - Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. - Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. - Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research: - Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. - Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. - Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact: - Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. - Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building: - Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. - Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.,

As a Compliance Technical Consultant at Cinque Technologies, you will be responsible for reviewing, suggesting, and leading the development of new features and functionalities in the existing AML/CFT products. Your primary focus will be to enhance the scalability of these products across various domains such as Banking, Insurance, Travel, Retail, Exchange, etc., in different geographies. By studying market demands and trends, you will play a vital role in facilitating the team and driving the company's expansion. Your performance will be evaluated based on the acquisition of new prospective clients from multiple domains and geographies, as well as finalizing deals with the company. To excel in this role, you should possess a degree in machine learning or related technical disciplines, or have equivalent industry experience. Deep expertise and practical hands-on skills in multiple machine learning techniques such as Natural Language Processing, Computer Vision, Reinforcement Learning, or Predictive Analytics are essential. Additionally, you should have in-depth knowledge and practical experience in designing enterprise-grade ML platforms that meet stringent security, compliance, performance/scalability, and operational requirements. Your role will also require practical hands-on coding skills in languages such as Python, SQL, and Java for developing advanced machine learning algorithms or key components of enterprise-grade machine learning platforms. With at least 5 years of total related industry experience, including 5+ years in leading large-scale machine learning engineering or data science initiatives in a large enterprise setting, you should be well-equipped to drive innovation in this field. Participation and contribution at industry AI/ML conferences, practical hands-on experience with industry-leading ML services/products like AWS AI/ML services, and familiarity with ML frameworks such as TensorFlow, PyTorch, MXNet, Keras, and Scikit-Learn are highly desirable. Experience with public clouds, excellent verbal and written communication skills, and the ability to effectively collaborate with senior executives and navigate complex organizational structures are also key requirements for this role. This is a full-time position with benefits including health insurance, paid sick time, and a provident fund. As part of the application process, you will be asked about your current salary, expected salary, and experience in the Fintech or Finance domain. A minimum of 3 years of experience in AI/ML is required for this role.,

Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelors or Master s degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community

Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelors or Master s degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community

Job description Working alongside Oliver Wyman consulting teams and partners, engaging directly with clients to understand their business challenges Exploring large-scale data anddesigning, developing, and maintaining data/software pipelines, and ETL processesfor internal and external stakeholders Explaining, refining, and developing the necessary architecture to guide stakeholders through the journey of model building Advocating application of best practices in data engineering, code hygiene, and code reviews Leading the development of proprietary data engineering, assets, ML algorithms, and analytical tools on varied projects Creating and maintaining documentation to support stakeholders and runbooks for operational excellence Working with partners and principals to shape proposals that showcase our data engineering and analytics capabilities Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art data engineering techniques in your domain Your Attributes, Experience Qualifications Bachelors or master s degree in a computational or quantitative discipline from a top academic program (Computer Science, Informatics, Data Science, or related) Exposure to building cloud ready applications Exposure to test-driven development and integration Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with ability to manage workload and meet deadlines in a fast-paced environment Collaborative team player Excellent verbal and written communication skills and command of English Willingness to travel Respect for confidentiality Technical Background Prior experience in designing and deploying large-scale technical solutions Fluency in modern programming languages (Python is mandatory; R, SAS desired) Experience with AWS/Azure/Google Cloud, including familiarity with services such as S3, EC2, Lambda, Glue Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle Experience with big data tools like Hadoop, Spark, Kafka Demonstrated knowledge of data structures and algorithms Familiarity with version control systems like GitHub or Bitbucket Familiarity with modern storage and computational frameworks Basic understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security Valued but not required: Compelling side projects or contributions to the Open-Source community Prior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Familiarity with containerization technologies, such as Docker and Kubernetes Experience with UI development using frameworks such as Angular, VUE, or React Experience with NoSQL databases such as MongoDB or Cassandra Experience presenting at data science conferences and connections within the data science community

Navaera Worldwide is a global, full-service firm specializing in advanced knowledge management products and services tailored to assist Financial organizations in enhancing operational efficiency, managing risk, detecting fraud, and gaining a competitive advantage. The company, a privately held entity, boasts a diverse client base across the globe, including major corporations within the financial services industry. Navaera Worldwide, under the brand Navaera Global Services, offers sophisticated business products and solutions to organizations of varying sizes. With offices situated across three continents, Navaera Worldwide's global headquarters is based in New York, with additional locations in Toronto, Canada, and Baroda, India. As a Specialist in Emerging Systems Engineering, you will be expected to possess a solid 3 to 5 years of experience range and be adept at working in areas such as Data Analytics, Computer vision, NLP, and OCR-related tasks. Your responsibilities will include data collection, dataset preparation, architecture modeling, model training/testing, and deployment. Additionally, you should have experience in managing digital data extraction and processing, creating training and testing pipelines with diverse data aspects, and developing model architectures from scratch or modifying pre-trained models. The ideal candidate must stay updated with the latest AI trends to ensure operational processes remain current. You will be required to identify opportunities for process enhancements, propose system modifications, and work with minimal technical supervision while efficiently managing multiple program priorities. Collaboration within a team environment is crucial, as you will be tasked with driving cross-team solutions that may have complex dependencies and requirements. Your qualifications should include a B.E./B.Tech in Computer Science/Statistics/IT/ECE stream, with an M.S. or Ph.D. in Applied Mathematics, Statistics, Computer Science, Operations Research, Economics, or equivalent. You should have 3-5 years of hands-on experience in data science, machine learning, and deep learning, along with proficiency in C/C++/Java/Python for developing machine learning and deep learning solutions. Experience in building and deploying Machine Learning solutions using various supervised and unsupervised ML algorithms is essential. Moreover, you should have at least 3-5 years of practical experience with Python and frameworks such as TensorFlow, PyTorch, or MXnet. A good command of ML libraries like scikit-learn, NumPy, pandas, and Keras, as well as natural language processing using NLTK, spaCy, and Gensim, is required. Strong communication and interpersonal skills, familiarity with decision science tools and techniques, excellent problem-solving abilities, and the capacity to work efficiently in a fast-paced, deadline-driven environment are all highly valued in this role. Demonstrating a strong work ethic, a sense of collaboration, and ownership is imperative for success within the organization.,

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

Dear Candidate, We are hiring a Computer Vision Engineer to develop AI-driven solutions for image recognition, object detection, and video analysis. The role requires expertise in deep learning, computer vision algorithms, and real-time processing techniques. Key Responsibilities: Develop and optimize computer vision models using OpenCV, TensorFlow, and PyTorch. Implement object detection, segmentation, and facial recognition algorithms. Process and analyze large-scale image and video datasets. Optimize deep learning models for real-time inference on edge devices. Collaborate with AI and software teams to integrate vision solutions into applications. Required Skills & Qualifications: Computer Vision Frameworks: OpenCV, DLIB, MediaPipe Deep Learning: TensorFlow, PyTorch, Keras Algorithms: CNNs, YOLO, Faster R-CNN, Mask R-CNN Programming: Python, C++, CUDA Edge AI: TensorRT, OpenVINO, NVIDIA Jetson Experience with autonomous systems, OCR, and SLAM is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

The Role and Responsibilities We have open positions ranging from Associate Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

Help empower our global customers to connect to culture through their passions. Why you'll love this role StockX is an established global startup headquartered in the USA with development offices in Bangalore India. In the Search & Recommendation team, we work together to productionalize custom machine-learning models that can drive product vision and customer impact at scale. We are looking for MLE who are product driven, and are passionate about making ML innovations in areas such as Ranking, Optimization, Natural Language Processing, Information Retrieval, Graph Learning, Reinforcement Learning to help improve the StockX buyer/seller experience! What you'll do Develop embeddings to collect salient signals of our customers, product, and user interactions. Extract real-time signals and multi-modality data (i.e, content and image) from our 5M+ product catalog images and 1M+ listings. Understand semantic content, aesthetic style, materials for retrieval, ranking and optimization. Build a real-time, in-session personalization recommendation system. Implement and compare supervised learning models (i.e, LR, GBDT, and DNNs) or ensembles of models, to improve metrics, often with multiple contending objectives (i.e, relevance, degree of personalization, average value of orders, repeated frequencies/purchases). Develop models with custom architecture or objective functions that target StockX-specific problems, such as recommendation system, personalized search, revenue optimization, seller fairness, seasonality, etc. Develop brand-new learning frameworks for query suggestions to understand buyer experience. Apply the latest advances in deep learning and machine learning to improve buyer and seller experiences on StockX. Prototype, optimize, and productionize large-scale ML models that help deliver key results in search experience. Conduct A/B experiments to validate ML models and pipelines. Work closely with product managers, Data scientists/engineers, full-stack engineers, and designers on product teams to deliver content to tens of millions of users. About you Experience with object-oriented or functional software development Experience working with AWS or other cloud providers Experience with big data platforms like Spark or Databricks Experience with machine learning libraries such as TensorFlow, PyTorch, or MXNet You have dealt with data exploration, analysis, and feature engineering You have relentlessly high standards for the products you deliver Work effectively in an agile development process You have a postgraduate degree in Computer Science or related engineering fields plus 3+ machine learning experience, or 5+ years of practical machine learning experience. Experience with Kubernetes and Docker for productionalizing models You have experience in building machine learning systems at scale. You have experience in using AWS Cloud Platform, Databricks and/or OpenSearch. You have experience in building production search, recommendations, advertising, or general e-commerce systems. About StockX StockX is proud to be a Detroit-based technology leader focused on the large and growing online market for sneakers, apparel, accessories, electronics, collectibles, trading cards, and more. StockX's powerful platform connects buyers and sellers of high-demand consumer goods from around the world using dynamic pricing mechanics. This approach affords access and market visibility powered by real-time data that empowers buyers and sellers to determine and transact based on market value. The StockX platform features hundreds of brands across verticals including Jordan Brand, adidas, Nike, Supreme, BAPE, Off-White, Louis Vuitton, Gucci collectibles from brands including LEGO, KAWS, Bearbrick, and Pop Mart and electronics from industry-leading manufacturers Sony, Microsoft, Meta, and Apple. Launched in 2016, StockX employs 1,000 people across offices and verification centers around the world. Learn more at www.stockx.com. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. This job description is intended to convey information essential to understanding the scope of the job and the general nature and level of work performed by job holders within this job. However, this job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities or working conditions associated with the position. StockX reserves the right to amend this job description at any time. StockX may utilize AI to rank job applicant submissions against the position requirements to assist in determining candidate alignment.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Interested in accelerating machine learning and artificial intelligence on mobile devices for millions of usersCome join our team. We are building software platforms that enable users of Qualcomms silicon to construct optimized neural networks and machine learning algorithms. We are looking for software engineers with a machine learning or compiler background who will help us build these software platforms. In this role, you will construct and tune machine learning frameworks, build compilers and tools, and collaborate with Qualcomm hardware and software engineers to enable efficient usage of Qualcomms silicon for machine learning applications. Minimum qualifications: Bachelors degree in Engineering, Information Systems, Computer Science, or related field. Programming in C/C++ 0 to 10 years of software engineering or related work experience Preferred qualifications: Experience in machine learning frameworks such as MxNet/NNVM/TVM, Pytorch, Tensorflow, Caffe OR experience in compilers with an interest in machine learning Deep knowledge of software engineering Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Interested in accelerating machine learning and artificial intelligence on mobile devices for millions of usersCome join our team. We are building software platforms that enable users of Qualcomms silicon to construct optimized neural networks and machine learning algorithms. We are looking for software engineers with a machine learning or compiler background who will help us build these software platforms. In this role, you will construct and tune machine learning frameworks, build compilers and tools, and collaborate with Qualcomm hardware and software engineers to enable efficient usage of Qualcomms silicon for machine learning applications. Minimum qualifications: Bachelors degree in Engineering, Information Systems, Computer Science, or related field. Programming in C/C++ 2 to 4 years of software engineering or related work experience Preferred qualifications: Experience in machine learning frameworks such as MxNet/NNVM/TVM, Pytorch, Tensorflow, Caffe OR experience in compilers with an interest in machine learning Deep knowledge of software engineering Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Senior Engineer: Senior Data Scientist (LLM / Transformer): Responsibilities: 1. Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience. 2. Design and implement AI safety and guardrails in the API layer working closely with researchers. 3. Collaborate with cross-functional teams to understand their data needs and develop solutions that meet those needs. 4. Stay updated with the latest trends and advancements in data science, machine learning, and Generative AI space. Qualifications: 1. Bachelors degree in Computer Science, Statistics, Mathematics, or a related field with 8+ years of relevant workingexperience, or Masters degree in the same with 5+ years of working experience. 2. Experience with machine learningfundamentals, with workingknowledge of Python and experience with deep learning frameworks such as Pytorch, TensorFlow, JAX or MXNet 3. Required hands-on experience with designand implementation ofapplications using Large Language Models (LLM). More specifically: Substantial prior programming experiencein languages suchas R, Python, SPARK, SQL. Comfort with professional software development process and GitHub. Google PaLM, OpenAI GPT, LLaMA, orsimilar models. LangChain, LlamaIndex, or similarframeworks. Advanced prompt engineering. Retrieval Augmented Generation (RAG). Vector databases (GCP Vector Search, ChromaDB, Experiences related to AWS services such as SageMaker,

The Role and Responsibilities We have open positions ranging from Associate Data Engineer to Lead Data Engineer, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data engineering track, you will be primarily responsible for developing and monitoring high-performance applications that can rapidly deploy latest machine learning frameworks and other advanced analytical techniques at scale. This role requires you to be a proactive learner and quickly pick up new technologies, whenever required. Most of the projects require handling big data, so you will be required to work on related technologies extensively. You will work closely with other team members to support project delivery and ensure client satisfaction. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with clients to understand their business challenges Exploring large-scale data and designing, developing, and maintaining data/software pipelines, and ETL processes for internal and external stakeholders Explaining, refining, and developing the necessary architecture to guide stakeholders through the journey of model building Advocating application of best practices in data engineering, code hygiene, and code reviews Leading the development of proprietary data engineering, assets, ML algorithms, and analytical tools on varied projects Creating and maintaining documentation to support stakeholders and runbooks for operational excellence Working with partners and principals to shape proposals that showcase our data engineering and analytics capabilities Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art data engineering techniques in your domain Your Attributes, Experience Qualifications Bachelor's or masters degree in a computational or quantitative discipline from a top academic program (Computer Science, Informatics, Data Science, or related) Exposure to building cloud ready applications Exposure to test-driven development and integration Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with ability to manage workload and meet deadlines in a fast-paced environment Collaborative team player Excellent verbal and written communication skills and command of English Willingness to travel Respect for confidentiality Technical Background Prior experience in designing and deploying large-scale technical solutions Fluency in modern programming languages (Python is mandatory; R, SAS desired) Experience with AWS/Azure/Google Cloud, including familiarity with services such as S3, EC2, Lambda, Glue Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle Experience with big data tools like Hadoop, Spark, Kafka Demonstrated knowledge of data structures and algorithms Familiarity with version control systems like GitHub or Bitbucket Familiarity with modern storage and computational frameworks Basic understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security Valued but not required: Compelling side projects or contributions to the Open-Source community Prior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Familiarity with containerization technologies, such as Docker and Kubernetes Experience with UI development using frameworks such as Angular, VUE, or React Experience with NoSQL databases such as MongoDB or Cassandra Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Roles and levels We are hiring for engineering role across the levels from Associate Data Engineer to Lead Data Engineer level for experience ranging from 0-8 years. In addition to the base salary, this position may be eligible for performance-based incentives.

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Interview Process The application process will include testing technical proficiency, case study, and team-fit interviews. Please include a brief note introducing yourself, what youre looking for when applying for the role, and your potential value-add to our team. Roles and levels In addition to the base salary, this position may be eligible for performance-based incentives. We offer a competitive total rewards package that includes comprehensive health and welfare benefits as well as employee assistance programs.

In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods onlarge scale data. B.E/B.Tech/MSin Machine Learning, Computer Science,Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, or Tensorflow Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus Can yousay Yes, I will! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods on largescale data. Good understanding on statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, Tensorflow. Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus

Job overview: In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? experience with developing solutions using machine learning, operation research and pattern searching methods on large scale data. B.E/B.Tech/MS in Machine Learning, Computer Science, Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models like hierarchical models, stochastic models, time series, survival and econometric models Expert in at least one of the deep learning frameworks such as PyTorch, MxNet, or Tensor flow Hands-on experience in using Spark (Scala or Py spark) to process data at large scale and database schema design for ML pipelines a must Contribution to open-source ML packages/research publications will be a huge bonus

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Interview Process The application process will include testing technical proficiency, case study, and team-fit interviews. Please include a brief note introducing yourself, what youre looking for when applying for the role, and your potential value-add to our team.

The Role and Responsibilities We are looking to hire an Associate Director in Data Science & Data Engineering Track. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. In the data engineering track, you will be primarily responsible for developing and monitoring high-performance applications that can rapidly deploy latest machine learning frameworks and other advanced analytical techniques at scale. This role requires you to be a proactive learner and quickly pick up new technologies, whenever required. Most of the projects require handling big data, so you will be required to work on related technologies extensively. You will work closely with other team members to support project delivery and ensure client satisfaction. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background (Data Science) Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required : Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Technical Background (Data Engineering) Prior experience in designing and deploying large-scale technical solutions Fluency in modern programming languages (Python is mandatory; R, SAS desired) Experience with AWS/Azure/Google Cloud, including familiarity with services such as S3, EC2, Lambda, Glue Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle Experience with big data tools like Hadoop, Spark, Kafka Demonstrated knowledge of data structures and algorithms Familiarity with version control systems like GitHub or Bitbucket Familiarity with modern storage and computational frameworks Basic understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security Valued but not required: Compelling side projects or contributions to the Open-Source community Prior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Familiarity with containerization technologies, such as Docker and Kubernetes Experience with UI development using frameworks such as Angular, VUE, or React Experience with NoSQL databases such as MongoDB or Cassandra Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence