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data/ml ops engineer

data ml ops engineer

NTT DATA, Inc.

<div>
 
 We are looking for a MLOps Engineer / DataOps Engineer with Cloud / Databricks experience. The role will be responsible for seamless flow of information throughout the company, maintaining and managing the production data pipelines.
 
 
 You will be working across a variety of tasks, primarily cloud engineering, establishing best practice and building out our Databricks Data Lakehouse. You will also be provisioning and maintaining the data clusters and data catalogs, monitoring existing pipelines.
 
 
 
 
 
 
 
 
 Job Description
 
 
 
 DataOps Responsibilities
 
 
 <ul>
 <li>
 Manage and optimize data pipelines and operations within the Databricks platform and cloud-based data lakes.
 </li>
 <li>
 Perform DML operations, data exports/imports, and schema management.
 </li>
 <li>
 Monitor data server health, investigate anomalies, and resolve performance issues.
 </li>
 <li>
 Analyze execution logs and troubleshoot data-related problems.
 </li>
 <li>
 Manage user access and ensure data security and compliance.
 </li>
 <li>
 Conduct regular database cleanup and optimization activities.
 </li>
 <li>
 Tune database objects and storage formats for performance and efficiency.
 </li>
 <li>
 Audit and enhance query performance; refactor tables or views as needed.
 </li>
 <li>
 Collaborate with platform and product teams to translate business needs into data solutions.
 </li>
 <li>
 Document data workflows, access policies, and operational procedures.
 </li>
 </ul>
 
 
 MLOps Responsibilities
 
 
 <ul>
 <li>
 Design and maintain end-to-end ML pipelines for training, validation, deployment, and monitoring.
 </li>
 <li>
 Automate model deployment using CI/CD practices and tools
 </li>
 <li>
 Monitor model performance, drift, and resource usage in production environments.
 </li>
 <li>
 Collaborate with Data Scientists to operationalize models and ensure reproducibility.
 </li>
 <li>
 Manage model versioning, rollback strategies, and deployment readiness.
 </li>
 <li>
 Implement observability and alerting for ML systems using tools like Prometheus and Grafana.
 </li>
 <li>
 Ensure compliance with data governance and model auditability standards.
 </li>
 <li>
 Support post-deployment troubleshooting and continuous improvement of ML systems.
 </li>
 </ul>
 
 
 Knowledge and Attributes:
 
 
 <ul>
 <li>
 Proficient in both SQL and NoSQL systems at scale.
 </li>
 <li>
 Strong programming skills in Python and/or Scala.
 </li>
 <li>
 Hands-on experience with Databricks, ETL pipelines, and data warehousing.
 </li>
 <li>
 Deep understanding of data modeling, schema design, joins, and key relationships.
 </li>
 <li>
 Skilled in database performance tuning and high-availability configurations.
 </li>
 <li>
 Strong analytical and algorithmic problem-solving capabilities.
 </li>
 <li>
 Effective communicator with the ability to collaborate across Engineering, Product, Operations, and Support teams.
 </li>
 <li>
 Demonstrates a proactive learning mindset and adaptability to evolving technologies.
 </li>
 <li>
 Capable of holistic system thinking across applications, databases, OS, and storage.
 </li>
 <li>
 Experienced in CI/CD pipeline design, automation tooling, and source code management.
 </li>
 <li>
 Familiar with deployment and release management best practices.
 </li>
 <li>
 Highly organized with strong planning, documentation, and project management skills.
 </li>
 <li>
 Client-focused with a commitment to delivering business outcomes.
 </li>
 <li>
 Detail-oriented and collaborative, with the ability to work effectively in team environments.
 </li>
 </ul>
 
 
</div>

Data/ML Ops Engineer

Infosys

<div>
 Technical skills
 
 
 <ul>
 <li>
 Programming: Python, R, SQL
 </li>
 <li>
 ML algorithms:
 </li>
 <li>
 Statistical ML algorithms
 </li>
 <li>
 Deep Neural Network architectures
 </li>
 <li>
 Model ensembling
 </li>
 <li>
 Generative AI models
 </li>
 <li>
 ML for Responsible AI
 </li>
 <li>
 AI domains - NLP, speech, computer vision, structured data
 </li>
 <li>
 Learning patterns &ndash; supervised, unsupervised, reinforcement learning
 </li>
 <li>
 Tools for data analysis, auto ML, model deployment &amp; scaling, model fine tuning
 </li>
 <li>
 Knowledge of different Model fine tuning approaches for Large models
 </li>
 <li>
 Knowledge of datasets, pre-built models available in open community and 3rd party providers
 </li>
 <li>
 Knowledge of software development &amp; architectures
 </li>
 <li>
 Knowledge of hyperscalers &amp; their AI capabilities &ndash; Azure, AWS, GCP
 </li>
 <li>
 Knowledge of Model Quantization and Pruning
 </li>
 <li>
 Past experience playing a Data Scientist role Technical skills
 </li>
 <li>
 Programming: Python, R, SQL
 </li>
 <li>
 ML algorithms:
 </li>
 <li>
 Statistical ML algorithms
 </li>
 <li>
 Deep Neural Network architectures
 </li>
 <li>
 Model ensembling
 </li>
 <li>
 Generative AI models
 </li>
 <li>
 ML for Responsible AI
 </li>
 <li>
 AI domains - NLP, speech, computer vision, structured data
 </li>
 <li>
 Learning patterns &ndash; supervised, unsupervised, reinforcement learning
 </li>
 <li>
 Tools for data analysis, auto ML, model deployment &amp; scaling, model fine tuning
 </li>
 <li>
 Knowledge of different Model fine tuning approaches for Large models
 </li>
 <li>
 Knowledge of datasets, pre-built models available in open community and 3rd party providers
 </li>
 <li>
 Knowledge of software development &amp; architectures
 </li>
 <li>
 Knowledge of hyperscalers &amp; their AI capabilities &ndash; Azure, AWS, GCP
 </li>
 <li>
 Knowledge of Model Quantization and Pruning
 </li>
 <li>
 Past experience playing a Data Scientist role
 </li>
 </ul>
</div>

Associate Data Scientist

Amazon

<div>
 
 
 DESCRIPTION
 
 
 
 
 TOC (Transportation Operation Center) is the central command and control center for &lsquo;Transportation Execution&rsquo; across the Amazon Supply Chain network supporting multiple geographies like NA, India and EU. It ensures hassle free, timely pick-up and delivery of freight from vendors to Amazon fulfillment centers (FC) and from Amazon FCs to carrier hubs. In case of any exceptions, TOC steps in to resolve the issue and keeps all the stakeholders informed on the proceedings. Along with this tactical problem solving TOC is also charged with understanding trends in network exceptions and then automating processes or proposing process changes to streamline operations. This second aspect involves network monitoring and significant analysis of network data.
 
 
 Overall, TOC plays a critical role in ensuring the smooth functioning of Amazon transportation and thereby has a direct impact on Amazon&rsquo;s ability to serve its customers on time.
 
 
 Purview of a Trans Ops Specialist
 
 
 A Trans Ops Specialist at TOC facilitates flow of information between different stakeholders (Trans Carriers/Hubs/Warehouses) and resolves any potential issues that impacts customer experience and business continuity. Trans Ops Specialist at TOC works across two verticals &ndash; Inbound and Outbound operations.
 
 
 Inbound Operations deals with Vendor/Carrier/FC relationship, ensuring that the freight is picked-up on time and is delivered at FC as per the given appointment. Trans Ops Specialist on Inbound addresses any potential issues occurring during the lifecycle of pick-up to delivery.
 
 
 Outbound Operations deals with FC/Carrier/Carrier Hub relationship, ensuring that the truck leaves the FC in order to delivery customer orders as per promise. Trans Ops Specialist on Outbound addresses any potential issues occurring during the lifecycle of freight leaving the FC and reaching customer premises.
 
 
 A Trans Ops Specialist provides timely resolution to the issue in hand by researching and querying internal tools and by taking real-time decisions. An ideal candidate should be able to understand the requirements/be able to analyze data and notice trends and be able to drive Customer Experience without compromising on time. The candidate should have the basic understanding of Logistics and should be able to communicate clearly in the written and oral form. Trans Ops Specialist should be able to ideate process improvements and should have the zeal to drive them to conclusion.
 
 
 
 Responsibilities Include, But Are Not Limited To:
 
 
 
 <ul>
 <li>
 Communication with external customers (Carriers, Vendors/Suppliers) and internal customers (Retail, Finance, Software Support, Fulfillment Centers)
 </li>
 <li>
 Ability to pull data from numerous databases (using Excel, Access, SQL and/or other data management systems) and to perform ad hoc reporting and analysis as needed is a plus.
 </li>
 <li>
 Develop and/or understand performance metrics to assist with driving business results.
 </li>
 <li>
 Ability to scope out business and functional requirements for the Amazon technology teams who create and enhance the software systems and tools are used by TOC.
 </li>
 <li>
 Must be able to quickly understand the business impact of the trends and make decisions that make sense based on available data.
 </li>
 <li>
 Must be able to systematically escalate problems or variance in the information and data to the relevant owners and teams and follow through on the resolutions to ensure they are delivered.
 </li>
 <li>
 Work within various time constraints to meet critical business needs, while measuring and identifying activities performed.
 </li>
 <li>
 Excellent communication, both verbal and written as one may be required to create a narrative outlining weekly findings and the variances to goals, and present these finding in a review forum.
 </li>
 <li>
 Providing real-time customer experience by working in 24*7 operating environment.
 
 
 </li>
 </ul>
 A day in the life
 
 
 
 About The Hiring Group
 
 
 
 Job responsibilities
 
 
 A day in the life
 
 
 
 About The Hiring Group
 
 
 
 Job responsibilities
 
 
 
 
 BASIC QUALIFICATIONS
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree
 </li>
 <li>
 10-24 months of work experience.
 </li>
 <li>
 Good communication skills - Trans Ops Specialist will be facilitating flow of information between external teams
 </li>
 <li>
 Proficiency in Advanced Excel (pivot tables, vlookups)
 </li>
 <li>
 Demonstrated ability to work in a team in a very dynamic environment
 
 
 </li>
 </ul>
 
 
 PREFERRED QUALIFICATIONS
 
 
 
 
 <ul>
 <li>
 Logistics background and lean/six sigma training is a plus
 </li>
 <li>
 Proficient in SQL
 
 
 </li>
 </ul>
 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 
 
 Company
 
 - Amazon Dev Center India - Hyderabad
 
 
 Job ID: A2868615
</div>

Transportation Representative, AV

Virtusa

<div>
 Python
 
 
 We are looking for a talented Senior Software Developer with strong Python skills. You will join our AI
 
 
 Solutions team. We focus on creating advanced AI systems in the Electrification field. In this role,
 
 
 you will work with AI/ML engineers, data scientists, and cloud architects. Together, you will develop
 
 
 robust, scalable software solutions using the latest AI technologies. This is a great chance to work
 
 
 where AI innovation meets highperformance backend systems and cloud-native development.
 
 
 
 Responsibilities
 
 
 
 Write highquality, testable, and maintainable Python code using object-oriented programming
 
 
 (OOP), SOLID principles, and design patterns.
 
 
 Develop RESTful APIs and backend services for AI/ML model serving using FastAPI.
 
 
 Collaborate with AI/ML engineers to integrate and deploy Machine Learning, Deep Learning, and
 
 
 Generative AI models into production environments.
 
 
 Contribute to software architecture and design discussions to ensure scalable and cient
 
 
 solutions.
 
 
 Implement CI/CD pipelines and adhere to DevOps best practices for reliable and repeatable
 
 
 deployments.
 
 
 Design for observability, incorporating structured logging, performance monitoring, and alerting
 
 
 mechanisms. Optimize code and system performance, ensuring reliability and robustness at scale.
 
 
 Participate in code reviews, promote clean code practices, and mentor junior developers when
 
 
 needed.
 
 
 
 Required Qualifications
 
 
 
 Bachelor or Master degree in Computer Science, IT, or a related field.5+ years of handson experience in software development, with a focus on Python. Deep understanding of OOP concepts, software architecture, and design patterns.
 
 
 Experience with backend web frameworks, preferably FastAPI.
 
 
 Familiarity with integrating ML/DL models into software solutions.
 
 
 Practical experience with CI/CD, containerization (Docker), and version control systems (Git).
 
 
 Exposure to MLOps practices and tools for model deployment and monitoring.
 
 
 Strong collaboration and communication skills in crossfunctional engineering teams. Familiarity with cloud platforms like AWS (e.g., Sagemaker, Bedrock) or Azure (e.g., ML Studio,
 
 
 OpenAI Service).
 
 
 
 Preferred Qualifications
 
 
 
 Experience in Rust is a strong plus.
 
 
 Experience working on highperformance, scalable backend systems.
 
 
 Exposure to logging/monitoring stacks like Prometheus, Grafana, ELK, or OpenTelemetry.
 
 
 Understanding of data engineering concepts, ETL pipelines, and processing large datasets.
 
 
 Background or interest in the Power and Energy domain is a plus.
 
 
 Mandatory Skills
 
 
 Python
 
 
 AI/ML model serving using FastAPI.
 
 
 ML/DL models
 
 
 MLOps practices
</div>

Python Developer

HackerRank

<div>
 HackerRank helps thousands of companies like OpenAI, NVIDIA, Mercedes and Amazon hire developers based on their skills vs. pedigree, and also nurtures a community of millions of developers to upskill themselves to become next-gen developers.
 
 
 The people at HackerRank care deeply about their work and have an extremely intense work ethic. In many companies, speed &amp; quality is a tradeoff. At HackerRank, it&rsquo;s not -- we expect you to ship in about half the time that most competent people think is possible while maintaining a standard of quality you&rsquo;d proudly sign your name on. The only way to make this happen is if you truly love your craft and are deeply committed to growth.
 
 
 
 About The Role
 
 
 
 We are seeking a Staff AI Scientist with deep expertise in machine learning fundamentals and a proven track record of building and evaluating advanced AI systems. This role is for someone who thrives at the intersection of data science, statistics, and ML engineering, with an emphasis on dataset rigor, metric design, and evaluation methodology.
 
 
 At the staff level, you will set the direction for how we evaluate AI systems, work across teams to ensure scientific rigor is balanced with product and engineering needs, and deliver both datasets and pipelines that stand up to scrutiny.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Dataset Preparation &amp; Evaluation
 </li>
 <ul>
 <li>
 Design, prepare, and curate high-quality evaluation datasets with defensible methodology.
 </li>
 <li>
 Define criteria for dataset construction, ensuring statistical rigor, reproducibility, and fairness.
 </li>
 <li>
 Develop new metrics and evaluation frameworks to measure model performance in nuanced ways.
 </li>
 </ul>
 <li>
 Model Evaluation &amp; ML Engineering
 </li>
 <ul>
 <li>
 Evaluate LLMs and other pre-trained models using carefully chosen datasets and metrics.
 </li>
 <li>
 Build scalable pipelines for training, fine-tuning, and benchmarking models.
 </li>
 <li>
 Contribute to projects involving fine-tuning, retrieval-augmented generation (RAG), and other adaptation methods.
 </li>
 </ul>
 <li>
 Cross-Functional Leadership
 </li>
 <ul>
 <li>
 Partner with product and engineering to align scientific rigor with business outcomes.
 </li>
 <li>
 Define evaluation standards and ML lifecycle practices that raise the bar across the company.
 </li>
 <li>
 Mentor scientists and engineers, guiding best practices in experimentation, statistics, and ML development.
 
 </li>
 </ul>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Education: Master&rsquo;s degree (PhD preferred) in Computer Science, Statistics, Machine Learning, or a related quantitative field.
 </li>
 <li>
 Strong background in mathematical and statistical foundations of machine learning (probability, linear algebra, optimization, experimental design).
 </li>
 <li>
 Demonstrated experience in end-to-end ML lifecycle: dataset preparation, model training, evaluation, deployment, and monitoring.
 </li>
 <li>
 Proven expertise in evaluation dataset design and metric creation, not just using existing benchmarks but knowing when and how to improve them.
 </li>
 <li>
 Experience with LLM evaluation, fine-tuning, and RAG, with the engineering skills to build production-ready pipelines.
 </li>
 <li>
 Track record of strategic impact at a staff or principal level setting evaluation and research standards across teams.
 
 
 </li>
 </ul>
 
 Even better if you have
 
 
 
 <ul>
 <li>
 Publications, open-source contributions, or widely adopted benchmarks in ML/AI.
 </li>
 <li>
 Prior experience shaping AI evaluation frameworks at an organizational or industry level.
 </li>
 <li>
 Comfort working at the interface of science, engineering, and product.
 
 
 </li>
 </ul>
 
 You will thrive in role if
 
 
 
 <ul>
 <li>
 You define gold-standard evaluation datasets and metrics that internal teams adopt as a standard.
 </li>
 <li>
 You ship datasets and pipelines that are statistically rigorous, reproducible, and scalable.
 </li>
 <li>
 You elevate the organization&rsquo;s ML practice by embedding sound statistical and scientific methodology into product and engineering work.
 </li>
 <li>
 You are recognized as a thought leader who sets strategy while still contributing technically at depth.
 
 
 </li>
 </ul>
 
 Want to learn more about HackerRank?
 
 Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.
 
 
 HackerRank is a proud equal employment opportunity and affirmative action employer. We provide equal opportunity to everyone for employment based on individual performance and qualification. We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
 
 
 Linkedin | X | Blog | Instagram | Life@HackerRank
 
 
 
 Notice To Prospective HackerRank Job Applicants
 
 
 
 <ul>
 <li>
 Our Recruiters use @hackerrank.com email addresses.
 </li>
 <li>
 We never ask for payment or credit check information to apply, interview, or work here.
 </li>
 </ul>
</div>

Staff AI Scientist

Blue Yonder

<div>
 
 Overview &amp; Scope
 
 
 
 <ul>
 <li>
 Leading AI-driven Global Supply Chain Solutions Software Product Company and one of Glassdoor&rsquo;s
 </li>
 <li>
 &ldquo;Best Places to Work&rdquo;
 </li>
 <li>
 We are seeking a highly skilled and motivated Data Science Consultant to join our Supply Chain
 </li>
 <li>
 Management team. The ideal candidate will leverage data-driven insights to optimize supply chain
 </li>
 <li>
 processes, improve decision-making, and drive business results. You will work closely with crossfunctional
 </li>
 <li>
 teams, utilizing advanced data analytics, machine learning, and optimization techniques to
 </li>
 <li>
 enhance supply chain efficiency, forecast demand, and solve complex operational challenges.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Data Analysis &amp; Modeling: Analyze large, complex data sets related to demand forecasting, supply
 </li>
 <li>
 planning to uncover actionable insights.
 </li>
 <li>
 Machine Learning: Apply statistical and machine learning techniques to forecast demand which would
 </li>
 <li>
 include
 </li>
 <li>
 Data ingestion, data visualization and insights, verifying the integrity of data used for analysis
 </li>
 <li>
 Feature engineering, configuring forecasting models
 </li>
 <li>
 Fine tune forecasting model
 </li>
 <li>
 Present results in a clear manner
 </li>
 <li>
 Supply Chain Optimization: Implement optimization algorithms to improve supply chain efficiency, reduce
 </li>
 <li>
 costs, and enhance service levels.
 </li>
 <li>
 Consulting &amp; Advisory: Serve as a subject matter expert (SME) for supply chain analytics, advising
 </li>
 <li>
 stakeholders on best practices, tools, and strategies for effective supply chain management.
 </li>
 <li>
 Process Improvement: Identify inefficiencies within the supply chain and recommend data-driven
 </li>
 <li>
 strategies for continuous improvement.
 
 
 </li>
 </ul>
 
 What We Are Looking For
 
 
 
 <ul>
 <li>
 Educational Background: Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Industrial
 </li>
 <li>
 Engineering, Operations Research, Supply Chain Management, or a related field.
 </li>
 <li>
 Experience: 5-12 years of experience in data science or Supply Chain Operations Analytics, or worked on
 </li>
 <li>
 forecasting projects leveraging statistical/ML models; experience with data visualization tools
 </li>
 <li>
 Technical Skills: Proficiency in data science tools and programming languages such as Python, R, SQL, and
 </li>
 <li>
 experience with supply chain management platforms/processes. Good, applied statistics skills, such as
 </li>
 <li>
 distributions, statistical testing, regression, etc
 </li>
 <li>
 Machine Learning: Hands-on experience with machine learning techniques/algorithms (e.g., regression,
 </li>
 <li>
 classification, clustering) and optimization models.
 </li>
 <li>
 Industry Knowledge: Familiarity with supply chain processes such as demand forecasting, inventory
 </li>
 <li>
 management, procurement, logistics, and distribution.
 </li>
 <li>
 Analytical Thinking: Strong problem-solving skills with the ability to analyze complex data sets and
 </li>
 <li>
 translate insights into actionable recommendations.
 </li>
 <li>
 Personal competencies
 </li>
 <li>
 Ability to work independently and as part of a team in a consulting environment.
 </li>
 <li>
 Attention to detail, with the ability to manage large data sets and complex analysis.
 </li>
 <li>
 Communication: Excellent verbal and written communication skills to present findings clearly to non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Our Values
 
 
 
 If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success &ndash; and the success of our customers. Does your heart beat like ours? Find out here: Core Values
 
 
 All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
</div>

Staff Data Scientist I - Supply Chain Operations Analytics

Arcana

<div>
 
 
 About the Role
 
 
 
 The HR Operations Associate at Arcana will work closely with business and engineering teams to support and scale people operations. This is a hands-on, fast-paced role focused on employee experience, HR operations, and process excellence. You will be a key point of contact for employees and play a critical role in ensuring HR processes are smooth, timely, and consistent.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Own end-to-end onboarding operations: documentation, coordination, checklists, and employee readiness.
 </li>
 <li>
 Support HR operational processes, including attendance/leave tracking, HRIS updates, and employee records.
 </li>
 <li>
 Serve as the first point of contact for employee queries with empathy, professionalism, and confidentiality.
 </li>
 <li>
 Support employee engagement initiatives/events, celebrations, surveys, and help drive follow-ups.
 </li>
 <li>
 Contribute to HR projects and process improvements; identify opportunities to simplify and automate workflows.
 </li>
 <li>
 Coordinate with Finance and Legal teams on addendums, contracts, and policy updates.
 </li>
 <li>
 Support onboarding and exit operations for expatriate employees (if applicable).
 </li>
 <li>
 Assist with HR audits/ISO documentation and ensure accurate record maintenance.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Master&rsquo;s/Bachelor&rsquo;s degree in HR or related field.
 </li>
 <li>
 0&ndash;1 year of experience in HR Ops/People Operations. MBA HR freshers are strongly encouraged to apply.
 </li>
 <li>
 Strong communication and relationship-building skills.
 </li>
 <li>
 Highly organised, detail-oriented, and able to manage multiple priorities.
 </li>
 <li>
 Proactive, resourceful, and a strong team player.
 </li>
 <li>
 Proficient in MS Office, HRIS tools, and general HR technology.
 </li>
 </ul>
 
 
</div>

Human Resources Associate

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