7 Numerical Optimization Jobs

We are looking for enthusiastic individuals who thrive on self-motivation and excel in first-principles thinking. In the ever-evolving world of AI, brimming with daily innovations, we seek individuals adept at swiftly navigating through solutions and conquering challenges with zeal. Responsibilities: - Be responsible for driving cutting-edge research projects in NLP and Computer Vision. - Leverage state-of-the-art techniques to design and implement innovative solutions. - Document and communicate thought processes, technical findings, and evaluation results. - Implement and fine-tune state-of-the-art foundational models (deep learning or classical ML models). - Collaborate with ML engineers, designers, software engineers, editorial team, and product managers in delivering high-impact ML solutions. - Mentor and guide junior engineers and scientists. Requirements: - Bachelors or Masters in AI/ML, Computer Science, Statistics, or other relevant fields. - Depth of knowledge in Natural Language Processing and/or Computer Vision. - Industry experience in using TensorFlow or PyTorch to implement or finetune multimodal deep learning models. - Strong understanding of statistics, linear algebra, probability theory, and numerical optimization. - Strong programming skills in Python preferably in a production environment. - Proven experience in defining problems from real-world scenarios (often ambiguous) and implementing creative solutions.,

Endovision is dedicated to enhancing the diagnostic accuracy of upper GI endoscopists through the use of deep learning and computational modeling, ultimately contributing to improved healthcare outcomes. As a Data Science Intern based in New Delhi, you will play a crucial role in developing end-to-end machine learning models to address real-world challenges within the industry. In this on-site internship position, you will work on implementing cutting-edge AI technologies, leveraging state-of-the-art research papers, and contributing to the company's intellectual property. You will be involved in building AI-first products and collaborating with research scientists and engineers at Endovision and its partner institutions. The primary focus areas will include deep learning, computer vision, and graphics, particularly in the context of endoscopy. Ideal candidates for this role should possess experience in Computer Vision and Deep Learning, with a strong foundation in neural networks such as CNNs, RNNs, autoencoders, and transfer learning methods. Proficiency in Python and its scientific libraries, familiarity with Machine Learning techniques, and knowledge of Deep Learning frameworks like Keras, TensorFlow, and PyTorch are essential requirements. Strong analytical and problem-solving skills, along with excellent communication abilities, are key attributes for success in this role. Candidates pursuing a Bachelor's or Master's degree in Computer Science, Statistics, or a related field are encouraged to apply. Experience with end-to-end machine learning projects would be advantageous. Preferred candidates will have the ability to independently implement and evaluate ideas using modern deep learning tools like Python, PyTorch, and GPU-enabled compute. Additionally, having a track record of implementing or publishing research papers in reputable academic conferences related to deep learning and computer vision applications will be highly valued. A positive attitude, strong teamwork skills, and effective communication capabilities are essential qualities for individuals joining our dynamic team at Endovision.,

DESCRIPTION Amazon Health Services (One Medical) About Us: At Health AI, we're revolutionizing healthcare delivery through innovative AI-enabled solutions. As part of Amazon Health Services and One Medical, we're on a mission to make quality healthcare more accessible while improving patient outcomes. Our work directly impacts millions of lives by empowering patients and enabling healthcare providers to deliver more meaningful care. Role Overview: We're seeking an Applied Scientist to join our dynamic team in building state of the art AI/ML solutions for healthcare. This role offers a unique opportunity to work at the intersection of artificial intelligence and healthcare, developing solutions that will shape the future of medical services delivery. Key job responsibilities . Lead end-to-end development of AI/ML solutions for Amazon Health organization, including Amazon Pharmacy and One Medical . Research, design, and implement state-of-the-art machine learning models, with a focus on Large Language Models (LLMs) and Visual Language Models (VLMs) . Optimize and fine-tune models for production deployment, including model distillation for improved latency . Drive scientific innovation while maintaining a strong focus on practical business outcomes . Collaborate with cross-functional teams to translate complex technical solutions into tangible customer benefits . Contribute to the broader Amazon Health scientific community and help shape our technical roadmap BASIC QUALIFICATIONS - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing PREFERRED QUALIFICATIONS - Experience in healthcare or medical informatics - Publication record in top-tier ML conferences/journals - Expertise in model optimization and distributed computing - Experience with AWS services and cloud computing - Knowledge of healthcare data privacy and security requirements Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

DESCRIPTION Are you passionate about solving complex logistics challenges that directly impact millions of customers Our Logistics Analytics team is at the forefront of revolutionizing delivery experiences through data-driven solutions and innovative technology. As a Applied Scientist, you will join a team dedicated to optimizing our delivery network, ensuring customers receive their packages reliably and efficiently. We are seeking an enthusiastic, customer centric professional with good analytical capabilities to drive impactful projects, implement advanced scheduling solutions, and develop scalable processes. In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of last-mile delivery. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity. This role offers the opportunity to make a significant impact on one of the world's most sophisticated logistics networks while working with pioneering technology and data science applications. BASIC QUALIFICATIONS - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing PREFERRED QUALIFICATIONS - Experience using Unix/Linux - Experience in professional software development Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

DESCRIPTION Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company Do you enjoy collaborating in a diverse team environment If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a Sr. manager of Applied Science who can lead a team of talented scientists to build advanced algorithmic systems that help manage the safety of millions of transactions every day. You will also spearhead initiatives to leverage Generative AI technologies to revolutionize our fraud detection capabilities and create next-generation risk prevention solutions Key job responsibilities - Lead a team of scientists in developing machine learning and statistical techniques to create scalable risk management systems, including exploration of GenAI applications - Guide team strategy in analyzing Amazon's historical business data to identify risk patterns and trends that inform business decisions - Partner with senior leaders to frame business problems, establish scientific vision, and execute strategic roadmaps across the organization - Direct research initiatives in novel machine learning approaches and ensure successful implementation of promising solutions - Oversee the design, development, and evaluation of highly innovative risk management models - Build and maintain strategic partnerships with software engineering teams to ensure successful real-time model implementations and new feature creations - Develop and maintain relationships with operations staff to optimize risk management operations - Drive the establishment of scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation - Provide clear, compelling management reporting on team progress, model performance, and business impact. - Hire, grow, and develop excellent scientific and analytic talents within the BRP Payment Risk team. BASIC QUALIFICATIONS - A Master in Computer Science, Machine Learning, Statistics, Operations Research or relevant field - 8+ years of building models for business application experience - Experience programming in Java, C++, Python or related language - Good written and spoken communication skills - Experience of building/developing teams, direct and shape the team plan, culture and strategy. - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing PREFERRED QUALIFICATIONS - A PhD in Computer Science, Machine Learning, Statistics, Operations Research or relevant field - 10+ years of industry experience in predictive modeling and analysis as a scientist or science manager - Experience in managing managers - Machine Learning breadth and depth - Ability to think creatively and solve complex business and technical problems - Skills in SQL/Python/R (or similar) - Demonstrated track record of cultivating effective working relationships and driving collaboration across multiple technical and business teams - Experience in managing cross-functional projects Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Job Title: Lead Quant Analyst, Credit Quants About the Team: DBRS Morningstar Credit Ratings, LLC is registered with the U.S. Securities and Exchange Commission as a nationally recognized statistical rating organization (NRSRO). DBRS Morningstar Credit Ratings issues credit ratings on a variety of security types including corporate and structured finance securities. This Morningstar subsidiary aims to increase market transparency by providing the highest-quality ratings, securities research, monitoring services, operational risk assessments, data, and tools. DBRS Morningstar is a global credit ratings business, formed through the July 2019 acquisition of DBRS by Morningstar, Inc., the ratings business is the fourth-largest provider of credit ratings in the world. DBRS Morningstar is committed to empowering investor success, serving the market through leading-edge technology and raising the bar for the industry. DBRS Morningstar is a market leader in Canada, the U.S. and Europe in multiple asset classes. DBRS Morningstar is driven to bringing more clarity, diversity of opinion, and responsiveness to the ratings process. DBRS Morningstars approach and size provide the agility to respond to customers needs, while being large enough to provide the necessary expertise and resources. The Role: As a Quant Analyst you will execute proprietary research pertaining to building data building various types of credit rating models, such as default models, cashflow models, capital models, regression models covering asset classes of ABS, CMBS, Covered Bond, RMBS, Structured Credit, Corporates, Financial Institutions and Sovereigns. The Credit Ratings Modeling team will collaborate with members from the Credit Ratings, Credit Practices, Independent Review, Data and Technology teams to create class leading models that are as innovative as they are easy to understand in the marketplace. You will be expected to adopt an "iron sharpens iron" attitude where the focus is on making everyone better. The ideal candidate will demonstrate Quant research skills in Credit Modeling alongside Quant Modeling skills such as statistics, Machine Learning, numerical optimization & software engineering skillset within Fintech eco space. This position reports to the Senior Manager of Quantitative Research, Technology. Responsibilities: Support methodology development, Quant Model builds & enhancements for core Quant products as credit predictive models, etc. Participate in building next generation of credit modelling. Maintain and enhance proprietary Python libraries related to model building Leverage structured and unstructured datasets to build new Quant frameworks that would help analysts in informed decision making. Assisting development of Analytics-based solutions, taking ownership of the design and development of solutions to scale information ingestion, storage, computation (training/inference), validation. Participate in analyst conversations for understanding ongoing analyst issues. Requirements: 4 to 5 years of investment research / rating agencies experience with emphasis on fixed income research / analysis, credit modelling. CFA, CQF or postgraduate degree in finance, economics, mathematics, statistics is highly desired. Experience developing Financial Engineering/ Statistical applications on cloud. Experience of statistical models (Regression, Monte Carlo simulations, Numerical Optimization etc.) Experience of developing Quant Models using Python. Experience engineering models on big data. Understanding of both business and technical requirements, and the ability to serve as a conduit between rating team, research and technology Familiarity fixed income. Morningstar is an equal opportunity employer About Us Morningstar DBRS is a leading provider of independent rating services and opinions for corporate and sovereign entities, financial institutions, and project and structured finance instruments globally. Rating more than 4,000 issuers and 60,000 securities, it is one of the top four credit rating agencies in the world. Morningstar DBRS empowers investor success by bringing more transparency and a much-needed diversity of opinion in the credit rating industry. Our approach and size allow us to be nimble enough to respond to customers' needs in their local markets, but large enough to provide the necessary expertise and resources they require. Market innovators choose to work with us because of our agility, tech-forward approach, and exceptional customer service. Morningstar DBRS is the next generation of credit ratings. If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker. Morningstars hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. While some positions are available as fully remote, weve found that were at our best when were purposely together on a regular basis, typically three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, youll have tools and resources to engage meaningfully with your global colleagues. R11_DBRSRatingsGmbHIndia DBRS Ratings GmbH, Branch India Legal Entity Show more Show less

SENIOR OPTIMIZATION ENGINEER Hyderabad Role Senior Optimization Engineer Contract type Permanent About the role As a Senior Optimization Engineer you provide technical expertise in the area of numerical optimization of thermo-fluid systems which are core to the Company's business this includes trade-off and optimize energy efficiency, production cost and operating economy. You engage with global product teams to solicit business needs and convert those into computational decision-making workflows, methods and tools to radically impact how company's products are designed, deployed and operated. Key targets include improving engineering effectiveness as well as developing disruptive, innovative methods for model-based design and operation of company's systems. You also take active part in product development to support design engineers in adopting and using new methods and tools. You also work closely with other teams in Systems, Controls, ML/AI COE, including teams responsible for model development (to drive the development of optimization-friendly thermo-fluid models) and controls engineering (to promote the use of computational optimization strategies (MPC, RTO) as needed). We are offering you We are committed to offering competitive benefits programs for all of our employees and enhancing our programs when necessary. A dynamic and international work environment in a company with high technology products. A strong growth strategy and people who are passionate about what they do. Requirements Education MEng or PhD in a relevant Engineering discipline (e.g., applied mathematics, mechanical or chemical engineering) with 5+ years of experience. Skills and qualifications Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs), including attention to reliable convergence of such problems. Proficient with the mathematical theory (applied mathematics, numerical analysis and functional analysis), algorithmic foundations (notably existence and convergence proofs), and methods/tools for numerical optimization (SQP, interior point method, etc.) of large-scale systems. Experience from using common algorithms/solvers for large-scale gradient-based non-linear programs, e.g., IPOPT, CONOPT, KNITRO, and WORHP, including their respective applicability to different types of problems. Experience from formulating and solving discrete optimization problems and using common algorithms, including CPLEX and Gurobi. Familiarity with physics-based modeling principles and best practices of thermo-fluid systems, such as vapor compression cycles or power plants. Familiarity and experience with development of computational platforms and tools in Python or equivalent. Familiarity with using HPC and cloud-based platforms for computation at scale. Demonstrated ability to work as part of a multidisciplinary team and an entrepreneurial attitude towards technological innovation in a global environment. Self-starter who is well-organized in an international team environment, with proven communication skills. Responsibilities Deployment. Support that methods and tools developed in the group impact the company's business through engagement in global product projects, including capture and formulation of computational problems arising in such projects. Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for large-scale numerical optimization are based on sound mathematical foundations and are deployed to match the needs of the company's business, including contributing to the architecture, development, testing and documentation of the methods and tools developed in the group. Modeling for optimization. Support development of mathematical models for thermo-fluid systems are built based on principles and best practices that secure reliable application of numerical optimization algorithms. Talent. Support development and training of staff within company's product teams and within the Computational Engineering group; contribute to talent pipeline by supervising student internships and theses.