דרושים Research Scientist Ssg Science ב-אמזון ב-הודו

As a Research Analyst (RA), you'll collaborate with experts to develop ML solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll build scalable solutions, write high-quality code, and develop state-of-the-art ML models. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with ML models. This will require collaboration with local and global teams, which have process and technical expertise. Therefore, RA should be a self-starter who is passionate about discovering and solving complicated problems, learning complex systems, working with numbers, and organizing and communicating data and reports.Key job responsibilities
• Scoping, driving and delivering complex projects across multiple teams.
• Performs root cause analysis by understand the data need, get data / pull the data and analyze it to form the hypothesis and validate it using data.
• Conducting a thorough analysis of large datasets to identify patterns, trends, and insights that can inform the development of NLP applications.
• Developing and implementing machine learning models and deep learning architectures to improve NLP systems.
• Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements
• Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap
• Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry
• Coordinate design efforts between Sciences and Software teams to deliver optimized solutions
• Ability to thrive in an ambiguous, uncertain and fast moving ML usecase developments.
• Mentor Junior Research Analyst (RAs) and contribute to RA hiring

- • Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics)
- • 3+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms
- • Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory
- • Strong analytical thinking
- • Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills
- • Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations.

- • Master's degree with specialization in ML, NLP or Computer Vision preferred
- • 3+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis)
- • Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in Data science, ML and Statistics

Key job responsibilities
Design, develop, evaluate and deploy, innovative and highly scalable ML models
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenanceLeading projects and mentoring other scientists, engineers in the use of ML techniques

- 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

- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience applying theoretical models in an applied environment

An ideal candidate will be an expert in the areas of machine learning, operations research, and statistics. With expertise in applying theoretical models in an applied environment relying heavily on the latest advances in machine learning, optimization, stochastic modeling, and engineering. The candidate will be expected to work on numerous aspects, such as feature engineering, modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models. Challenges will involve dealing with very large data sets and requirements on throughput.Key job responsibilities
- Create experiments and prototype implementations of new learning algorithms and prediction techniques

- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 3+ years of building machine learning models or developing algorithms for business application experience
- 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in professional software development
- Experience implementing algorithms using toolkits and self-developed code

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 5+ years of building machine learning models or developing algorithms for business application experience
- Knowledge of architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members

Key job responsibilities- You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning
- You are able to use reasonable assumptions, data, and customer requirements to solve problems.
- You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects.
- You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs.
- You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughlyA day in the life
You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.

- Experience building machine learning models or developing algorithms for business application
- Experience programming in Java, C++, Python or related language
- PhD, or Master's degree
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience in computer architecture

- Experience with Linux/Unix

As a Senior Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers.Key job responsibilities- You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty.
- You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones.- You set standards and proactively drive components to use and improve on state-of-the-art techniques.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with prompting techniques for LLMs

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- PhD in math/statistics/engineering or other equivalent quantitative discipline
- Experience with conducting research in a corporate setting
- Experience in patents or publications at top-tier peer-reviewed conferences or journals.

Key job responsibilities
Innovate in visual translation: Design, develop, and deploy state-of-the-art machine learning models for image translation, including text detection, recognition, and translation in images across multiple languages and scripts.Experiment and iterate: Design and execute experiments to evaluate the performance of different models across diverse image types, languages, and domains, and iterate quickly to improve results.
Build robust evaluation frameworks: Create comprehensive evaluation frameworks for assessing model performance across different languages, scripts (Latin, CJK, RTL, Indic), visual domains, and translation quality metrics.Drive scientific excellence: Publish your research at top-tier conferences.

- Experience programming in Java, C++, Python or related language
- Master's degree
- Experience researching about machine learning, deep learning, NLP, computer vision, data science

- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Have publications at top-tier peer-reviewed conferences or journals

Key job responsibilities
* Lead and innovate in applying advanced NLP and LLM techniques to solve complex language translation challenges in e-commerce, driving product-level improvements for our international marketplaces. Drive innovation on Image and Video translation.* Architect and implement novel, scalable machine learning solutions that enhance translation quality evaluation and improve translation pipeline efficiency across multiple teams and systems.* Spearhead cross-functional collaborations to define strategic project requirements, establish organization-wide success metrics, and deliver high-impact solutions aligning with broader business objectives.* Drive comprehensive data analysis to uncover non-obvious insights in multilingual data, relaying findings into actionable strategies that influence product roadmaps and capabilities for language technologies.* Pioneer and implement modeling techniques for machine translation quality assessment and pipeline optimization, leading the team's scientific agenda. Invent new methodologies when existing approaches fall short, advancing the state-of-the-art.* Serve as a recognized expert in LLM applications for e-commerce translation, communicating complex concepts to diverse stakeholders including senior leadership. Influence organization-wide adoption of innovative approaches in language translation technologies.* Actively mentor team members, elevating scientific capabilities and fostering a culture of innovation and rigorous inquiry in machine translation and evaluation.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 5+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.