Machine Learning Engineer Ii Core Engineering Salary India Jobs

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer Manager, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. Mentor and guide engineers, fostering knowledge sharing and best practices. What we are looking for? 8+ years of industry experience in data engineering. Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Data modelling and modern data platform design concepts Building and maintaining data platforms in Azure/AWS or GCP Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders.

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role As a Senior Full-Stack Engineer in the Machine Learning department, you will help build and scale product capabilities focused on AI-enabled experiences, experimentation, and optimization. This is a full-stack role for an engineer who is comfortable owning work across the stack while spending most of their time on backend development. You will contribute to initiatives related to personalization, intake experiences, and AI-powered product improvements, while partnering closely with adjacent teams to deliver practical, production-ready solutions. This role is a strong fit for someone who enjoys combining traditional software engineering with modern AI workflows and wants to work on systems that evolve through real-world usage and iteration. What You’ll Do Build backend-heavy full-stack solutions that support Javelin team initiatives Contribute to frontend development as needed to deliver end-to-end product functionality Work on LLM- and AI agent-related application features and integrations Help support and extend self-optimization capabilities connected to the intake bot and related workflows Collaborate with cross-functional partners and adjacent engineering teams on shared initiatives Practice specification-driven engineering, translating requirements into clear, well-scoped specs before and during implementation Write maintainable, production-quality code and contribute to st

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role The future of analytics isn't dashboards. It's intelligent systems that anticipate questions, surface insights, and help people make better decisions. We're looking for a Senior Analytics Engineer to help build that future at Pearl. In this role, you'll design and develop AI-powered analytics experiences that combine trusted enterprise data with modern AI capabilities, enabling business users to interact with data conversationally and uncover insights faster than ever before. You'll build production AI agents, create scalable semantic data models, develop intelligent analytics applications, and establish best practices for responsible AI across the Analytics organization. Working closely with Product, Engineering, and business leaders, you'll turn emerging AI technologies into real business capabilities that improve decision making across the company. This is an opportunity to help define how AI transforms analytics at Pearl while working on some of the most exciting technologies in data, LLMs, and agentic AI. What You’ll Do Build proactive analytics and AI solutions that surface actionable business insights, anticipate business needs, and enable smarter decision-making. Design and develop AI-powered analytics tools, including conversational interfaces that allow business users to query data using natural language. Build semantic data models and reusab

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services ( MS Azure, GCP preferred) , ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms. Successful ca

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. Team Description Reddit is poised to rapidly innovate and grow like no other time in its history. We’re currently hiring across multiple teams, some of these teams include: Ads ML Serving Team The Ads ML Serving team is part of Reddit’s Ads ML Platform, which builds the infrastructure and tools that power machine learning across Ads. This team focuses on creating a highly reliable, scalable, and efficient ML serving stack. Their work includes evolving long-term serving architecture, integrating closely with the ads serving stack, optimizing CPU/GPU performance, and building model velocity tools like observability libraries and model quality gating. Attribution & Identity Team The Attribution & Identity team builds products that help advertisers understand and measure the impact of their campaigns. They focus on attribution systems, identity solutions, and advertiser experimentation tools that improve performance insights and usability. Their goal is to make Reddit’s advertising platform more effective, transparent, and data-driven. Ads Growth Team The Ads Growth team drives initiatives to expand Reddit’s advertiser base, with a focus on Small to Medium Businesses (SMBs). We build and scale the technical founda

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. About Open Intelligence: Open Intelligence (OI) is one of WPP’s most strategic bets — a data and AI initiative at the intersection of machine learning, advertising technology, and audience insight, built to power the next generation of media intelligence. OI operates at real scale, running across the US and UK and expanding rapidly across EMEA and APAC. Our Copenhagen team has ~50 people, including 14+ data scientists and a strong engineering group. We’re flat, high-trust and fast-moving: strong opinions loosely held, teamwork over ego, aim high and have fun. Why we're hiring: Open Intelligence is accelerating the development of its core AI capabilities, and we are strengthening our applied-AI and engineering group in Copenhagen. We need a Data Engineer who can help bridge the gap between AI experimentation and production software engineering — working alongside data scientists and senior engineers to turn cutting-edge model research, multimodal embeddings, and agentic tools into scalable, robust, and well-architected components that power products across WPP globally. We are looking for a Data

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Did you know? Alternative investing has the potential to generate higher returns compared to traditional investments over the long term. AI and Machine Learning are revolutionizing the way alternative investments are managed and analyzed. Investors are using these technologies to gain insights, see opportunities, and optimize their investment strategies. Addepar is building solutions to support our clients' alternatives investment strategies. The alternatives data management product is a serverless, modular and terraformed stack. We're hiring a Senior Software Engineer to design, implement and deliver modern software solutions that ingest and process ML-extracted data. You will collaborate closely with cross-functional teams including data scientists and product managers to build intuitive solutions that revolutionize how clients experience alternatives operations. You will work closely with operations engineering on document-based workflow automation and peer engineering teams to define the tech stack. You will iterate quickly through cycles of testing a new product offering on Addepar. If you've crafted scalable systems, or worked with phenomenal teams on hard problems in financial data, or are just interested in solving reall

DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com . What You’ll Do: We are looking for a Software Engineer to help build and scale our core backend systems and data infrastructure. In this role, you will work hands-on to develop the foundational data pipelines, storage solutions, and robust architectures that drive our healthcare advertising solutions and support our core products, reporting APIs, and analytics initiatives. This is an excellent opportunity for a growth-oriented engineer to work with massive datasets, modern cloud technologies, and cross-functional teams to deliver high-performance, fault-tolerant solutions. Build & Operate: Develop, test, and maintain highly reliable, scalable, and cost-optimized distributed systems and data architectures. Enable Self-Service Data: Create automated ingestion, storage, and transformation pipelines that make it simple for downstream users to access and utilize new datasets. Empower Machine Learning: Design and operate data pipelines specifically tailored to support the complex workflows of our Data Scientists and Machine Learning Engineers. Drive Operational Excellence: Help implement and champion DataOps and DevOps practices across the team to ensure system reliability and smooth deployments. Contribute to Best Practices: Play an active role in establishing and refining formal data practices, architectures, and engineering standards for the organization. Cross-Functional Collaboration: Partner effectively with business stakeholders,

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed system The Team The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. Responsibilities and Duties Develop, own, and maintain tools and services to support the software org