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senior software engineer Jobs in Mangaluru

senior software engineer

associate software engineer Jobs in Mangaluru

associate software engineer

ai/ml scientist(operations research/optimization/simulation) Jobs in Mangaluru

ai/ml scientist(operations research/optimization/simulation)

applied scientist, india machine learning Jobs in Mangaluru

applied scientist, india machine learning

machine learning engineer

Glance

<div>
 
 
 What you will be doing
 
 
 
 We are looking for a Data Scientist who can operate at the intersection of
 
 classical machine learning
 
 ,
 
 large-scale recommendation systems
 
 , and
 
 modern agentic AI systems
 
 .
 
 
 You will design, build, and deploy intelligent systems that power Glance&rsquo;s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.
 
 
 
 Your responsibilities will include:
 
 
 
 
 Classical ML &amp; Recommendation Systems
 
 
 <ul>
 <li>
 Design and develop large-scale recommendation systems using advanced ML, statistical modelling, ranking algorithms, and deep learning.
 </li>
 <li>
 Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
 </li>
 <li>
 Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
 </li>
 <li>
 Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
 </li>
 <li>
 Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.
 </li>
 </ul>
 
 
 Agentic Systems &amp; Next-Gen AI
 
 
 <ul>
 <li>
 Build and experiment with
 
 agentic AI systems
 
 that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
 </li>
 <li>
 Apply
 
 LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models
 
 for semantic understanding, content classification, and user preference modelling.
 </li>
 <li>
 Design intelligent agents that can automate repetitive decision-making tasks&mdash;e.g., candidate generation tuning, feature selection, or context-aware content curation.
 </li>
 <li>
 Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.
 </li>
 </ul>
 
 
 Cross-functional impact
 
 
 <ul>
 <li>
 Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance&rsquo;s consumer experiences.
 </li>
 <li>
 Contribute to Glance&rsquo;s ML/AI thought leadership&mdash;blogs, case studies, internal tech talks, and industry conferences.
 </li>
 <li>
 Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
 </li>
 <li>
 Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
 </li>
 </ul>
 
 
 
 
 We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.
 
 
 You should have experience with:
 
 <ul>
 <li>
 Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
 </li>
 <li>
 Classical ML and deep learning techniques across NLP, sequence modelling, RL, clustering, and time series.
 </li>
 <li>
 Experience in deploying ML workflows/models in production system
 </li>
 <li>
 Big data processing (Spark, distributed data systems) and cloud computing.
 </li>
 <li>
 Designing end-to-end ML solutions&mdash;from prototype to production.
 </li>
 <li>
 Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s/master&rsquo;s in computer science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
 </li>
 <li>
 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
 </li>
 <li>
 Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
 </li>
 <li>
 Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
 </li>
 <li>
 Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
 </li>
 <li>
 Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
 </li>
 <li>
 Comfortable working in cross-functional teams.
 </li>
 <li>
 Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
 </li>
 <li>
 Excellent communication skills with the ability to simplify complex technical concepts.
 </li>
 </ul>
 
 
 
 We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.
 
 
 Our team includes engineers, physicists, economists, mathematicians, and social scientists&mdash;a great data scientist can come from anywhere.
 
</div>

Machine Learning Engineer III - Recommendation Systems

Myntra

<div>
 
 About The Company
 
 
 
 
 Who are we?
 
 
 
 Myntra is India&rsquo;s leading fashion and lifestyle platform, where technology meets creativity. As pioneers in fashion e-commerce, we&rsquo;ve always believed in disrupting the ordinary.
 
 
 We thrive on a shared passion for fashion, a drive to innovate to lead, and an environment that empowers each one of us to pave our own way. We&rsquo;re bold in our thinking, agile in our execution, and collaborative in spirit.
 
 
 Here, we create MAGIC by inspiring vibrant and joyous self-expression and expanding fashion possibilities for India, while staying true to what we believe in.
 
 
 We believe in taking bold bets and changing the fashion landscape of India. We are a company that is constantly evolving into newer and better forms and we look for people who are ready to evolve with us.
 
 
 From our humble beginnings as a customization company in 2007 to being technology and fashion pioneers today, Myntra is going places and we want you to take part in this journey with us.
 
 
 Working at Myntra is challenging but fun - we are a young and dynamic team, firm believers in meritocracy, believe in equal opportunity, encourage intellectual curiosity and empower our teams with the right tools, space, and opportunities.
 
 
 
 About Team
 
 
 
 The Myntra Data Science team is at the forefront of innovation, delivering cutting-edge solutions that drive significant revenue and enhance customer experiences across various touchpoints. Every quarter, our models impact millions of customers, leveraging real-time, near-real-time, and offline solutions with diverse latency requirements. These models are built on massive datasets, allowing for deep learning and growth opportunities within a rapidly expanding organization. By joining our team, you'll gain hands-on experience with an extensive e-commerce platform, learning to develop models that handle millions of requests per second with sub-second latency.
 
 
 We take pride in deploying solutions that not only utilize state-of-the-art machine learning techniques&mdash;such as graph neural networks, diffusion models, transformers, representation learning, optimization methods, and Bayesian modeling&mdash;but also contribute to the research community with multiple peer-reviewed publications.
 
 
 Roles and Responsibilities
 
 
 Design, Develop, and Deploy: Create and implement advanced machine learning models and algorithms to tackle complex business challenges across various domains, including Recommender Systems, Search, Computer Vision, Supply Chain Management (SCM), Pricing, Forecasting, Trend and Virality Prediction, Generative AI, and more.
 
 
 Technical Expertise: Demonstrate deep theoretical knowledge and practical expertise in one or more areas, such as Natural Language Processing (NLP), Computer Vision, Recommender Systems, and Optimization.
 
 
 Software Development: Develop robust, scalable, and maintainable software solutions for seamless model deployment.
 
 
 CI/CD Pipelines: Set up and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for automated testing, deployment, and model integration.
 
 
 Model Maintenance: Maintain and optimize machine learning pipelines, including data cleaning, feature extraction, and model training.
 
 
 Collaboration: Work closely with the Platforms and Engineering teams to ensure smooth deployment and integration of ML models into production systems.
 
 
 Data Management: Partner with the Data Platforms team to gather, process, and analyze data crucial for model development.
 
 
 Code Quality: Write clean, efficient, and maintainable code following best practices.
 
 
 Performance Optimization: Conduct performance testing, troubleshooting, and tuning to ensure optimal model performance.
 
 
 Continuous Learning: Stay up-to-date with the latest advancements in machine learning and technology, sharing insights and knowledge across the organization.
 
 
 
 Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Industry Experience: 5+ years with a Bachelor's degree, or 3+ years with a Master&rsquo;s/Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
 </li>
 <li>
 Machine Learning Expertise: At least 2 years of hands-on experience as a Machine Learning Engineer or a similar role.
 </li>
 <li>
 Production Deployment: Proven experience deploying machine learning solutions into production environments.
 </li>
 <li>
 Programming Skills: Strong proficiency in Python or equivalent programming languages for model development.
 </li>
 <li>
 ML Frameworks: Familiarity with leading machine learning frameworks (Keras, TensorFlow, PyTorch) and libraries (scikit-learn).
 </li>
 <li>
 CI/CD Tools: Experience with CI/CD tools and practices.
 </li>
 <li>
 Communication: Excellent verbal and written communication skills.
 </li>
 <li>
 Teamwork &amp; Independence: Ability to work collaboratively in a team environment or independently as needed.
 </li>
 <li>
 Workload Management: Strong organizational skills to manage and prioritize tasks, supporting your manager effectively.
 
 
 </li>
 </ul>
 Exceptional candidates are encouraged to apply, even if you don't meet every listed qualification. We're open to hiring individuals who demonstrate outstanding potential.
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Research Contributions: Publications or presentations in recognized Machine Learning and Data Science journals/conferences.
 </li>
 <li>
 Big Data Technologies: Experience with big data technologies like Spark or other distributed computing frameworks.
 </li>
 <li>
 Cloud Services: Proficiency in cloud platforms (AWS, Google Cloud) and an understanding of distributed systems.
 </li>
 <li>
 Generative AI Exposure: Familiarity with Generative AI models.
 </li>
 <li>
 Database Management: Experience with SQL and/or NoSQL databases.
 </li>
 <li>
 ML Orchestration: Knowledge of ML orchestration tools (Airflow, Kubeflow, MLFlow).
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 python, machine learning, recommendation system, forecasting, deployment, time series
 
 
 
 Required Education
 
 
 
 B.Tech
</div>

Senior Data Scientist

Microsoft

<div>
 
 Overview
 
 
 
 We are seeking a passionate and technically skilled Data Scientist II to join the Commerce &ndash; Platforms, Data, and Experiences (PDX) team. This team plays a pivotal role in shaping Microsoft&rsquo;s commerce data strategy, building scalable data platforms, and delivering actionable ML driven insights that drive business transformation across the ecosystem.
 
 
 As a Data Scientist II in PDX, you will work at the intersection of data engineering, data processing, and machine learning to solve complex business problems. You will collaborate with cross-functional teams to design experiments, build predictive models, and develop scalable solutions that enhance decision-making and customer experiences by producing descriptive, diagnostic, predictive and prescriptive insights.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement advanced analytics solutions to support commerce data platform initiatives including analytics based on Machine Learning Models.
 </li>
 <li>
 Partner with engineering and product teams to define data requirements and ensure high-quality data pipelines.
 </li>
 <li>
 Conduct exploratory data analysis, feature engineering, and model evaluation using structured and unstructured datasets.
 </li>
 <li>
 Ensure the models built are operable, scalable, extensible and performant.
 </li>
 <li>
 Develop dashboards, visualizations, and storytelling artifacts to communicate insights to stakeholders.
 </li>
 <li>
 Lead experimentation efforts to evaluate new features, forecasting, data quality and anomaly detection systems.
 </li>
 <li>
 Build extensible solutions on LLM models to improve productivity of engineers across the commerce organization.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Statistics, Mathematics, or related field.
 </li>
 <li>
 2+ years of experience in data science, analytics, or applied machine learning.
 </li>
 <li>
 Proficiency in Python, SQL, and ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Experience with cloud platforms (Azure preferred) and big data technologies.
 </li>
 <li>
 Strong understanding of statistical modeling, predictive analytics, and experimentation design.
 </li>
 <li>
 Excellent communication and stakeholder management skills.
 </li>
 <li>
 Demonstrated experience leveraging AI tools and technologies to enhance engineering effectiveness, coupled with a strong curiosity and commitment to continuous learning in the field of Artificial Intelligence.
 
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
</div>

Data Scientist II

Weekday AI (YC W21)

<div>
 
 This role is for one of the Weekday's clients
 
 
 
 
 Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)
 
 
 
 Min Experience: 4 years
 
 
 Location: Bangalore
 
 
 JobType: full-time
 
 
 We are looking for a Data Scientist to lead the end-to-end data science lifecycle&mdash;from problem definition and hypothesis development to model deployment planning and performance evaluation. This role focuses on building scalable, production-ready machine learning solutions that drive insights across content, audience, growth, and revenue use cases.
 
 
 You will work closely with product, editorial, growth, sales, and engineering teams to identify high-impact opportunities and translate complex data into actionable business outcomes.
 
 
 
 Requirements
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Own the complete data science workflow including problem framing, feature engineering, model development, validation, and deployment planning
 </li>
 <li>
 Develop and operationalize machine learning models for forecasting, personalization, churn prediction, attribution, ranking, and content intelligence
 </li>
 <li>
 Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic and entity modeling, summarization, and relevance scoring
 </li>
 <li>
 Design sales and advertising analytics solutions including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement
 </li>
 <li>
 Perform advanced statistical analysis including causal inference, A/B testing, experiment design, incrementality, and uplift measurement
 </li>
 <li>
 Partner with data engineering teams to develop scalable data pipelines and model training workflows
 </li>
 <li>
 Define and maintain unified KPIs and measurement frameworks to evaluate content performance and audience behavior across platforms
 </li>
 <li>
 Monitor model performance, detect drift, ensure robustness, fairness, and governance of deployed models
 </li>
 <li>
 Deliver executive-ready insights through dashboards, automated reports, and clear data storytelling
 </li>
 <li>
 Collaborate with cross-functional teams to prioritize initiatives with the highest business impact
 </li>
 <li>
 Contribute to code and design reviews, mentor peers, and raise analytical standards across the organization
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 
 
 Must-Have
 
 
 
 
 <ul>
 <li>
 4-7 years of applied data science experience delivering measurable business impact
 </li>
 <li>
 Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL
 </li>
 <li>
 Hands-on experience building and validating ML models including regression, classification, forecasting, clustering, recommendation systems, uplift models, and NLP-based solutions
 </li>
 <li>
 Solid foundation in statistics, probability, hypothesis testing, experimental design, and causal inference
 </li>
 <li>
 Experience working with large-scale datasets and cloud platforms such as AWS, Azure, or GCP
 </li>
 <li>
 Familiarity with BI and visualization tools like Tableau, Power BI, or Plotly
 </li>
 <li>
 Strong analytical thinking, communication, and data storytelling skills
 
 
 </li>
 </ul>
 
 
 Good-to-Have
 
 
 
 
 <ul>
 <li>
 Experience with deep learning frameworks such as TensorFlow or PyTorch
 </li>
 <li>
 Exposure to big data technologies like Spark, Hadoop, or Databricks
 </li>
 <li>
 Familiarity with MLOps practices, model monitoring, and production ML workflows
 
 
 </li>
 </ul>
 
 
 Education
 
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
 
 
 </li>
 </ul>
 
 Key Skills
 
 
 
 Data Science
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Pandas
 </li>
 <li>
 NLP
 </li>
 <li>
 Machine Learning
 </li>
 <li>
 SQL
 </li>
 <li>
 AWS
 </li>
 <li>
 Statistics
 </li>
 <li>
 Experimentation
 </li>
 </ul>
</div>

Data Scientist

<div>
 At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we&rsquo;ll give you what you need to make it happen. It won&rsquo;t always be easy, growing takes grit. But at ABB, you&rsquo;ll never run alone. Run what runs the world.
 
 
 This Position reports to:
 
 
 Principal Software Engineer
 
 
 
 
 
 
 
 What We Believe In
 
 
 
 Join us at ABB as we work together with a global team to transform society and industry, promoting a more productive and sustainable future.
 
 
 Our mission at ABB is to promote diversity and inclusion on every front, encompassing gender, sexual orientation, abilities, ethnicity, and generational perspectives. Together, we are embarking on a journey where each one of us, individually and collectively, welcomes and celebrates individual differences.
 
 
 ABB is a prominent global technology firm that facilitates the evolution of society and industry towards a more efficient, sustainable future. ABB has a rich history that spans over 130 years, contributing significantly through the four Industrial Revolutions and continues to shape the path of industry 4.0. By incorporating digital innovations within its electrification, robotics, automation, and motion offerings, ABB transforms technology to enhance performance capabilities significantly.
 
 
 
 Roles &amp; Responsibilities:
 
 
 
 This is a technical Leadership role in Cloud and AI platform, reporting to the Digital Solution Engineering Manager in ABB Ability&trade; Genix - industrial analytics and artificial intelligence Platform in business area Process Automation located in Bangalore. You will be leading the Product delivery team including Platform Services at Ability Innovation Center (AIC), home to the largest technology and engineering pool in ABB globally and is a part of ABB Global Industries and Services Private Limited, a subsidiary of ABB. It is based in Bangalore, the silicon-valley of India. Its unique infrastructure places research, development, engineering, and service teams under one roof, increasing collaboration and reducing time to market, with no compromise on quality.
 
 
 We are looking for a highly proficient Software Engineer to become part of our team, working on the development and improvement of ABB Ability&trade; Genix, particularly in areas like deployment automation, packaging, and essential technical skills. As a Software Engineer, you'll have the chance to connect with an accomplished team of engineers to advance technology initiatives, improve Agile Delivery, and bolster overall team effectiveness.
 
 
 Are you interested in a workplace that combines the aspects of technology, data, domain, and Industrial AI to build innovative analytics solutions for process automation customers? If you prioritize creativity and effective solutions, this could be the right team for you. Become part of ABB and take advantage of our varied global network as you collaborate with and guide our esteemed teams. Most importantly, push yourself each day to reach new heights. Let&rsquo;s write the future together.
 
 
 The work model for the role is: Hybrid
 
 
 
 You will be mainly accountable for:
 
 
 
 <ul>
 <li>
 Build LLM/agent workflows using LangChain, LangGraph, or similar frameworks; develop and refine prompts, conversational flows, and integrations for IIoT use cases; enhance model understanding of industry terminology and real-time data; collaborate with engineering teams and create supporting documentation.
 </li>
 <li>
 Oversee the creation of features associated with LLM frameworks and agent-based workflows; maintain effective communication with interdisciplinary teams; share regular updates on project progress; encourage a culture of collaboration; eliminate technical obstacles; and liaise with external partners.
 </li>
 <li>
 Promote continuous improvement within the team; identify opportunities to optimize Scrum processes; and provide coaching or training on Scrum practices.
 </li>
 <li>
 Align product, engineering, and stakeholder efforts to ensure cohesive delivery, smooth collaboration, and consistent execution across IIoT and AI-driven initiatives.
 
 
 </li>
 </ul>
 
 Qualifications for the role:
 
 
 
 <ul>
 <li>
 Hold a Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related technical field, with 3+ years of experience in NLP, machine learning, and chatbot development.
 </li>
 <li>
 Exhibit advanced knowledge of Python, particularly in application development with Flask or FastAPI, and showcase experience in rolling out production-ready systems on Kubernetes.
 </li>
 <li>
 Possess familiarity with IIoT concepts, protocols, and systems, along with the ability to design and implement scalable, secure web and REST API applications.
 </li>
 <li>
 Demonstrate proficiency in machine learning frameworks and programming languages, such as Python, TensorFlow, and PyTorch, along with experience in microservices architecture and asynchronous design methods.
 </li>
 <li>
 Possess practical knowledge of Azure cloud services, such as App Service, Cosmos DB, AKS, Cognitive Datalake, and Azure SQL Server.
 </li>
 <li>
 Be skilled in working with CI/CD pipelines for automated build, test, and deployment processes, ensuring scalable and maintainable software delivery.
 </li>
 <li>
 Exhibit effective communication, documentation, mentoring, and collaboration skills to assist in team development and knowledge exchange.
 
 
 
 </li>
 </ul>
 
 More About Us
 
 
 ABB&rsquo;s Digital business area enables customers to operate some of the world&rsquo;s largest and most complex industrial infrastructures, helping them outrun &ndash; leaner and cleaner.
 
 
 Become a part of our innovative team and advance your career by playing a role in creating impactful Industrial AI and Cloud applications and services that prioritize care.
 
 
 We value people from different backgrounds. Could this be your story? Apply today or visit www.abb.com to read more about us and learn about the impact of our solutions across the globe.
 
 
 
 Fraud Warning:
 
 Any genuine offer from ABB will always be preceded by a formal application and interview process.
 
 
 We never ask for money from job applicants.
 
 
 For current open positions you can visit our career website https://global.abb/group/en/careers and apply.
 
 
 Please refer to detailed recruitment fraud caution notice using the link https://global.abb/group/en/careers/how-to-apply/fraud-warning.
</div>

Software Engineer

Amadeus

<div>
 
 Job Title
 
 
 
 Data Scientist 3
 
 
 
 About The Role
 
 
 
 You will join a multidisciplinary team of software engineers, data engineers, data scientists, product specialists, and designers working on next-generation
 
 AI-powered solutions
 
 for airport and airline operations. As part of the Data Spark
 
 Agile Release Train
 
 , you will collaborate closely with colleagues in Nice and London.
 
 
 Your key responsibility will be to
 
 design, automate, and optimize machine learning workflows
 
 that power:
 
 
 <ul>
 <li>
 Real-time analytics and inferencing
 </li>
 <li>
 Predictive modeling
 </li>
 <li>
 ML foundations for generative AI capabilities
 
 
 </li>
 </ul>
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design, implementation, and maintenance of scalable, cloud-native ML pipelines (primarily on Microsoft Azure within a multi-cloud strategy) for batch and streaming workloads.
 </li>
 <li>
 Automate the end-to-end lifecycle of ML models: data preparation, experimentation, tuning, deployment, monitoring, and continuous improvement with a focus on reproducibility and governance.
 </li>
 <li>
 Collaborate with software engineers to ensure robust integration of ML models into production systems, including API contracts, SLAs, fallbacks, and graceful degradation strategies.
 
 
 </li>
 </ul>
 
 About The Ideal Candidate
 
 
 
 <ul>
 <li>
 Proven experience building and maintaining production-grade ML pipelines in cloud environments across real-world projects.
 </li>
 <li>
 Strong hands-on experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and solid understanding of model development patterns (supervised learning, time-series forecasting, model evaluation).
 </li>
 <li>
 Practical MLOps expertise with tools like Azure Machine Learning, MLflow, or similar platforms for experiment tracking, pipeline orchestration, and model deployment.
 </li>
 <li>
 Strong command of Python for production-grade deliveries, including testing, code reviews, documentation, packaging, and version control.
 </li>
 <li>
 Experience working in Agile teams (Scrum, SAFe).
 
 
 </li>
 </ul>
 
 
 
 Diversity &amp; Inclusion
 
 
 
 
 
 Amadeus aspires to be a leader in Diversity, Equity and Inclusion in the tech industry, enabling every employee to reach their full potential by fostering a culture of belonging and fair treatment, attracting the best talent from all backgrounds, and as a role model for an inclusive employee experience.
 
 
 Amadeus is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, race, ethnicity, sexual orientation, age, beliefs, disability or any other characteristics protected by law.
</div>

Data Scientist 3

<div>
 
 Overview
 
 
 
 Overview
 
 
 With the rapid acceleration of AI and the need to deliver trustworthy, high-performing models, Microsoft&rsquo;s Customer Experience (CXP) Data Science team is driving innovation at scale! Our mission is to advance AI capabilities through rigorous evaluations, fine-tuning, and large-scale experimentation to create intelligent, personalized experiences for customers worldwide. The CXP Data Science team is seeking passionate AI practitioners and data scientists to join agile, cross-functional teams working on cutting-edge model evaluation frameworks, optimization pipelines, and experimentation platforms that power Microsoft&rsquo;s AI ecosystem.
 
 
 We are looking for an
 
 Applied AI Scientist II
 
 to join our team! As a member of the Customer Experience Data Science organization at Microsoft, you will help us accelerate the company&rsquo;s own AI transformation. You will have the opportunity to partner directly with the engineering and product management groups responsible for managing the Dynamics 365 applications that power Microsoft&rsquo;s sales, marketing, and support platforms. You will apply advanced analytics, statistical modeling, machine learning and GenAI tools to uncover insights, drive action and deliver innovative solutions for complex business challenges.
 
 
 
 This Role Offers The Opportunity To
 
 
 
 <ul>
 <li>
 Collaborate across a diverse team of data scientists, engineers, and product managers
 </li>
 <li>
 Deepen your expertise in the evolving AI and ML landscape
 </li>
 <li>
 Drive meaningful impact for thousands of Microsoft sales, marketing and support platform users
 
 
 </li>
 </ul>
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Work with key stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes.
 </li>
 <li>
 Transform formulated problems into implementation plans by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results.
 </li>
 <li>
 Write robust, reusable, and extensible code to support analysis and modeling.
 </li>
 <li>
 Develop new ML and GenAI based models using advanced statistical, ML and LLM techniques.
 </li>
 <li>
 Lead the evaluation of various GenAI based solutions, diagnosing issues and identifying root causes to support potential fine-tuning or reinforcement learning based fixes.
 </li>
 <li>
 Use AI-powered tools in your daily work to accelerate coding, analysis, and other tasks.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Qualifications
 
 
 
 Required/Minimum Qualifications (RQs/MQs)
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
 </li>
 <ul>
 <li>
 OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
 </li>
 <li>
 OR equivalent experience.
 </li>
 </ul>
 <li>
 Expertise in Python , PySpark, and SQL, LLMs
 </li>
 <li>
 Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 
 </li>
 </ul>
 
 Additional Or Preferred Qualifications (PQs)
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Machine Learning, Data science, Mathematics, Statistics, Computer Science, or related field AND 5+ years related experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
 </li>
 <ul>
 <li>
 OR master&rsquo;s degree in data science, Mathematics, Statistics, Computer Science, or related field AND 4+ year(s) related experience
 </li>
 <li>
 OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, or related field AND 3+ year(s) related experience
 </li>
 </ul>
 <li>
 Experience in Spark and ability to write/maintain/understand declarative Spark code and to cleanly write and maintain SQL. Knowledge of finer operational aspects of Spark such as setting optimal cluster size, executor memory, number of executors etc. and experience in Azure Synapse/Databricks (or similar).
 </li>
 <li>
 Expertise in ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 </li>
 <li>
 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
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Data & Applied Scientist II

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