We're seeking a Head of Machine Learning to own and scale the ML function at Prodigal. This is the senior-most ML role in the company — partnering directly with the CTO as a peer technical leader, defining the multi-year ML vision, building and leading a world-class team, and translating cutting-edge research into production systems that move the needle for over 100 customers and millions of consumers. You'll set the bar for technical excellence, hire and develop the next generation of ML leaders, and shape what consumer finance intelligence looks like over the next decade. If you've operated at this level before — or are ready to step into it at a company where ML is the engine of the product — we want to talk.

Responsibilities:

• Own the ML function end-to-end — vision, roadmap, team, delivery, and measurable business impact across classical ML, NLP, GenAI, and Agentic AI
• Partner with the CTO as the senior ML leader to set company-wide technical direction and shape the long-term roadmap for Prodigal's Intelligence Engine
• Build and lead a high-performing ML organization — hire, mentor, and develop ML engineers, applied scientists, and tech leads across multiple pods
• Translate research into product — drive the application of LLMs, Agentic AI, the modern NLP stack, recommendation systems, and classical ML into production systems serving 100+ customers
• Set technical standards for model development, deployment, monitoring, evaluation, and experimentation that scale across the org
• Architect data and ML infrastructure in partnership with the platform and engineering teams to support large-scale training and reliable, low-latency inference
• Communicate strategy and outcomes clearly to the founders, board, customers, and broader engineering organization
• Represent Prodigal externally — at conferences, in research collaborations, and as a senior voice in the consumer finance AI community
• Stay at the frontier of ML and GenAI research, identifying where new techniques unlock product and business advantage
• Collaborate cross-functionally with product, engineering, GTM, and customer success leaders to ensure ML investment ties directly to revenue, retention, and customer outcomes

Requirements:

• 10+ years of experience in machine learning and software development at a tech or product company, with 4+ years leading ML teams (managing engineers and/or tech leads)
• Proven track record of shipping ML products in production at scale with measurable business impact
• Deep technical fluency across classical ML, deep learning, and the modern NLP/LLM stack — you can still go deep in design reviews, not just review at the surface
• Strong coding skills in Python. Hands-on with PyTorch, scikit-learn, Pandas, and Spark
• Demonstrated success hiring, mentoring, and growing ML talent — including team leads and senior engineers
• Strong executive communication and the ability to set technical direction with founders, peers, and the board
• A bias for outcomes — you connect model work to revenue, engagement, and operational metrics

Preferred Qualifications:

• Experience as a founding ML hire, ML lead, or applied science leader at a high-growth AI/ML product company
• Background in voice AI, conversational AI, speech, NLP on unstructured text, or fintech/lending domains
• Experience with cloud services (AWS), Databricks, and building scalable, distributed systems
• Track record of running A/B testing and experimentation programs at scale
• Patents, publications, or open-source contributions; strong institutional pedigree (IIT, BITS, NIT, IISc)
• Experience scaling an ML org through a hypergrowth phase

Job Benefits

• GenAI at the core – Lead the ML function at a company where AI isn't a feature, it's the product. Shape groundbreaking work that redefines consumer finance intelligence.
• World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
• Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
• Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
• Health insurance - Health always comes first. The health of your family is as important to us as it is to you. We offer insurance coverage for both you and your family.
• Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
• Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
• Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions, and challenge each other to do those extra push-ups or chug that 4th drink (of course, that's Nimbu Pani).

Meet Sangram (Cofounder and CTO) and hear his vision for Prodigal: https://www.youtube.com/embed/FTWlN9fwiIA?feature=shared

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who you are

We are looking for a highly motivated and analytical Data Scientist to join our growing data team. You will play a key role in extracting insights from large datasets, building predictive models, and supporting data-driven decision-making across departments.

What you'll do

• Collect, process, and analyze large datasets from multiple sources
• Build and deploy machine learning models to solve business problems
• Design and implement A/B tests and statistical analyses
• Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements
• Communicate complex data insights in a clear and actionable manner to stakeholders
• Develop dashboards and visualizations to monitor key metrics
• Stay current with the latest trends and technologies in data science and AI

What we're looking for

• Bachelor’s and or Master’s degree in Computer Science, Mathematics, Statistics, or related field
• 4+ years of proven experience as a Data Scientist or Data Analyst
• Strong knowledge of Python/R and SQL
• Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch)
• Experience with big data tools (e.g., Spark, Hadoop)
• Familiarity with data visualization tools
• Strong analytical, problem-solving, and communication skills

While not required, these are a plus:

• Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc)
• Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)

3 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

The below role is for our Bengaluru office. 

Director – Data Science 

Why Join Sigmoid? 

• Sigmoid provides the opportunity to push the boundaries of what is possible by seamlessly combining technical expertise and creativity to tackle intrinsically complex business problems and convert them into straight-forward data solutions. 
• Despite being continuously challenged, you are not alone. You will be part of a fast-paced diverse environment as a member of a high-performing team that works together to energize and inspire each other by challenging the status quo 
• Vibrant inclusive culture of mutual respect and fun through both work and play

Roles and Responsibilities: 

• Convert broad vision and concepts into a structured data science roadmap, and guide a  team to successfully execute on it. 
• Handling end-to-end client AI & analytics programs in a fluid environment. Your role will be a  combination of hands-on contribution, technical team management, and client interaction.
• Proven ability to discover solutions hidden in large datasets and to drive business results  with their data-based insights 
• Contribute to internal product development initiatives related to data science.
• Drive excellent project management required to deliver complex projects, including  effort/time estimation. 
• Be proactive, with full ownership of the engagement. Build scalable client engagement level  processes for faster turnaround & higher accuracy 
• Define Technology/ Strategy and Roadmap for client accounts, and guides implementation  of that strategy within projects 
• Manage the team-members, to ensure that the project plan is being adhered to over the  course of the project 
• Build a trusted advisor relationship with the IT management at clients and internal accounts  leadership. 

Mandated Skills: 

• A B-Tech/M-Tech/MBA from a top tier Institute preferably in a quantitative subject
• 15+ overall experience with 12+ years of hands-on experience in applied Machine Learning, AI and analytics
• Experience of scientific programming in scripting languages like Python, R, SQL, NoSQL, Spark with ML tools & Cloud Technology (AWS, Azure, GCP) 
• Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scrapy, BERT etc.
• Strong grasp of depth and breadth of machine learning, deep learning, data mining, and statistical concepts and experience in developing models and solutions in these areas
• Expertise with client engagement, understanding complex problem statements, and offering solutions in the domains of Supply Chain, Manufacturing, CPG, Marketing etc. 

Desired Skills: 

• Deep understanding of ML algorithms for common use cases in both structured and  unstructured data ecosystems. 
• Comfortable with large scale data processing and distributed computing 
• Providing required inputs to sales, and pre-sales activities 
• A self-starter who can work well with minimal guidance
• Excellent written and verbal communication skills

SLSQ127R200

As a Partner Solutions Architect (PSA) for India, you will work with the technical and sales team members who work directly with our customers. You will develop 'technical champions' within our top Partners, providing enablement on technical matters related to the Databricks product. Working with our partners, you will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark™, MLflow, and Delta Lake; and major public cloud infrastructure and services. the product. You will use this expertise to become a trusted advisor to C&SI partners.

The impact you will have:

• Provide partners with the level of enablement they need to assist their clients in evaluating and adopting Databricks including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem
• Engage with the partner technical community by leading workshops, seminars, and meet-ups
• You will be a Big Data Analytics expert on aspects of architecture and design and will share this with our partner network
• Show expertise by producing creative technical solutions and blog posts

What we look for:

• 8 years of customer facing experience working with external clients or partners across a variety of industry markets
• Core strength in either data engineering or data science
• Experience demonstrating technical concepts, including presenting and whiteboarding
• Experience developing architectures within a public cloud (AWS, Azure, or GCP)
• Hands on experience in SQL, Python, Scala, or Java
• Expertise in at least one of the following:
• Data Engineering technologies (Ex: Apache Spark™, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Job Description

We are looking for a Senior Data Scientist with a strong foundation in SQL/Python programming, data handling, and data wrangling to work on high-impact projects in the healthcare domain. This is a hands-on role involving advanced analytics, developing metrics and reports from large, complex datasets, and building scalable data solutions like solution workbenches.

The ideal candidate will demonstrate a strong aptitude for understanding business context, generating insights from data, and a proactive attitude toward learning and applying relevant data tools and techniques. A solid grasp of claims analytics, combined with the ability to work in the healthcare space and apply a wide range of quantitative and analytical methods to drive better business decisions, is essential. Experience or interest in Generative AI tools to enhance analytics workflows will be a key advantage.

Responsibilities

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

Bachelors or Masters degree in computer science, Statistics, Data Science, or a related
quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL
and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets
is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using
libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify
opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical
findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical
concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic
environment.

ISMS Responsibilities

• Comply with information security policies and processes
• Report security weaknesses, events or potential events, or other security risks, to the organization
• Execute all tasks related to information security management system as appropriate

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

Want to build the next generation of AI-powered analytics and intelligent agents for observability and security use cases? Passionate about leveraging cutting-edge machine learning, large language models, and GPU-accelerated inference to transform how organizations understand and act on their logs data? Come talk with us!

As a Senior Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, context engineering and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.

Location: Noida/ Bengaluru (Hybrid)

Responsibilities

• Design, implement, and optimize agentic AI components, including tools, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 6+ years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Experience with distributed systems and dealing with large amounts of data.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• Experience leading a team of engineers.
• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

About Us

Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.

Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Here’s a summary of the role:

Ready to build real-world AI solutions that actually make an impact?

You’ll take cutting-edge AI and GenAI concepts—like copilots, agents, and intelligent workflows—and turn them into scalable, production-ready systems used across sales, finance, customer success, and more. If you enjoy hands-on backend engineering, working with APIs, cloud platforms, and LLMs, and transforming ideas into high-performing AI-driven products, this role puts you right at the center of innovation.

Here’s a breakdown of what you’ll do (not all of it, just the important stuff):

• Build and scale backend services, APIs, and integrations that embed AI/GenAI into enterprise systems (CRM, ERP, BI)
• Develop LLM-powered solutions such as RAG pipelines, copilots, agents, and automation workflows
• Take AI solutions from concept to production—design, build, test, deploy, and monitor
• Collaborate with architects and business stakeholders to turn requirements into practical AI implementations
• Create and manage data pipelines to enable reliable, high-quality AI workflows
• Ensure solutions are secure, scalable, observable, and aligned with best practices

These are the essentials you’ll need to get an interview:

• 5+ years of experience in software or solutions engineering with production systems
• Strong programming skills in Python, Java, C#, or Node.js
• Hands-on experience with APIs, integrations (REST/webhooks), and backend development
• Practical experience working with LLMs/GenAI tools (e.g., OpenAI, LangChain, or similar)
• Experience with cloud platforms (preferably AWS), CI/CD, and containerization
• Solid understanding of AI/GenAI concepts like prompt engineering, RAG, or agents
• Ability to translate technical solutions into business impact and collaborate across teams

It would be great if you had these too, but we’ll support you if you don’t:

• Experience integrating AI into CRM, ERP, or analytics platforms
• Familiarity with MLOps/LLMOps concepts such as model lifecycle and monitoring
• Exposure to machine learning or data analytics tools (e.g., Scikit-learn, dashboards)
• Experience working in global or distributed teams
• Knowledge of AI governance, security, and responsible AI practices

Job Title: ML Full stack Engineer

 About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the  British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO? 

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Job Description:

CSQ326R35

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Minimum of 5+ years of relevant experience as a Data Scientist preferably working in a consulting role
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.

Offices: New York | Dallas | San Francisco | Lima | Bengaluru

The below role is for our Bengaluru office.

About the Role:

You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you.

Function:  Data Science and Analysis → Data Science / Machine Learning

Desired Skills & Competencies:

• Strong learning acumen
• Team Management
• High sense of ownership
• Ability to work in a fast-paced and deadline-driven environment
• Loves technology
• Highly skilled at Data Interpretation
• Problem solver
• Good exposure to machine learning concepts and algorithms
• Must be fluent with any one of Python, R, Java
• Strong in statistical & machine learning concepts
• Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn
• Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS)

Responsibilities:

• Hypothesis testing, insights generation, root cause analysis, factor analysis
• Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms
• Test/train the model, Improve Model accuracy, Monitor model performance
• Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA

Desired Experience & Education:

• 3 - 5 years of relevant Machine Learning experience.
• B. Tech from Tier-1 college / M.S or M. Tech is preferred in Computer Science, Information Technology, or similar degree.

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

The Role

We’re looking for a seasoned Staff Machine Learning Engineer to shape and scale the backbone of our production ML ecosystem. In this role, you will architect high-performing ML systems that power our geospatial intelligence platform, transforming large-scale satellite and aerial imagery into actionable insights. You’ll lead end-to-end ownership—from model deployment and MLOps to infrastructure design—while partnering closely with data science, platform engineering, and product teams to deliver reliable, scalable, and cost-efficient ML solutions. If you thrive at the intersection of deep technical expertise, system design, and cross-functional collaboration, this role is for you.

How you'll make an impact:

ML System Architecture & Production Deployment

• Design, build, and maintain end-to-end ML pipelines for batch processing of satellite and aerial imagery
• Deploy and scale ML models in production on AWS infrastructure, leveraging services like SageMaker, Bedrock,or custom-built solutions
• Implement MLflow for experiment tracking, model versioning, and model registry management
• Architect batch inference systems optimized for throughput and cost-efficiency
• Work with geospatial data formats and coordinate reference systems
• Collaborate with data scientists to transition models from research to production
• Partner with platform engineering to build scalable compute, GPU clusters, and storage layers

ML Operations & Reliability

• Implement comprehensive model monitoring systems to track performance degradation and data drift
• Design and execute canary deployments and A/B testing frameworks for safe model rollouts
• Build active learning pipelines to continuously improve model performance with minimal labeling effort
• Establish model evaluation frameworks and performance benchmarking processesCreate alerting and observability systems for production ML workloads

Technical Leadership

• Mentor ML engineers and data scientists on best practices for production ML
• Drive technical decision-making on ML infrastructure and tooling
• Collaborate with platform and data engineering teams to optimize the ML stack
• Establish engineering standards and contribute to architectural roadmaps

What we’re looking for:

• 5+ years of experience in machine learning engineering with 2+ years in a senior or lead capacity
• Proven track record deploying and maintaining ML systems in production using AWS services (SageMaker,Lambda, ECS/EKS, S3, etc.)
• Strong hands-on experience with tools like MLflow, WandB, or similar for experiment tracking and model management
• Deep expertise in image segmentation and computer vision techniques using frameworks like PyTorch or TensorFlow
• Production experience with ensemble models (xgboost, lightgbm, RF)

ML Operations Expertise

• Experience implementing model monitoring, drift detection, and alerting systems
• Hands-on experience with canary deployments, A/B testing and Shadow deployments for ML models
• Knowledge of active learning strategies and human-in-the-loop ML systems
• Strong understanding of model evaluation metrics, bias detection, and performance analysis

Technical Skills

• Expert-level Python programming with ML libraries (scikit-learn, PyTorch/TensorFlow, NumPy, pandas, etc)
• Experience with distributed batch processing frameworks (Airflow, Step Functions, Argo Workflows, Spark,Dask, Ray or similar)
• Proficiency with AWS ML ecosystem and infrastructure-as-code (Terraform, CloudFormation)
• Hands-on experience with dataset versioning tools such as DVC, LakeFS, Delta Lake, Quilt, or Pachyderm
• Strong software engineering fundamentals: unit/integration testing, CI/CD, version control, observability, designpatterns
• Experience with containerization (Docker, Kubernetes) for model deployment
• Good to have experience with ML Orchestration tools like Kubeflow, Vertex AI, etc
• Nice to have experience with GPUs: scheduling GPU jobs, optimizing GPU performance, memory profiling

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.