About the team 

A reliable, privacy-safe, and scalable data foundation is critical to Roku’s rapidly growing advertising business. The Ad Data Activation organization builds the identity systems, device graph pipelines, audience platforms, insights tooling, and data collaboration capabilities that power targeting, measurement, and reporting across Roku Ads. 

We are hiring a Senior Machine Learning Engineer to help drive intelligence across these systems. You will work at the intersection of large-scale data platforms, applied machine learning, and generative AI — building capabilities that make Roku's advertising data more actionable for internal teams and advertisers. This includes building core generative AI platform features for Roku Advertising, while also applying traditional ML techniques to improve accuracy, automation, and decisioning across the ecosystem. If you enjoy working across data, ML, and new Gen-AI patterns — and want to shape how intelligence shows up inside Roku Ads — this role is for you. 

About the role 

In this role, you will design, build, and productionize intelligent capabilities that combine agentic Gen-AI systems with conventional ML pipelines across identity resolution, audience modeling, attribution, and optimization workflows. You will work with massive datasets, develop pipelines that transform raw signals into actionable features, and partner closely with product, data science, and platform teams. 

What you will be doing 

• Develop scalable and effective ML models and data pipelines to power identity, graph enrichment, audience segmentation, and campaign performance intelligence 

• Design and run experiments, measure impact, and translate results into product decisions and customer outcomes 

• Build and productionize agentic, generative-AI features — including reporting and insights agents, campaign-monitoring agents (with human-in-the-loop controls), and a semantic layer for reliable, natural-language analytics 

• Improve automation, reliability, and scalability across model training, feature engineering, deployment, and monitoring frameworks 

• Work closely with software and ML engineers to deliver end-to-end solutions from data ingestion through downstream systems 

• Partner with senior stakeholders to shape ML and Gen-AI strategy for Ad Data Activation — identifying the right problems for AI, ensuring safety, and driving advertiser productivity. 

We’re excited if you have 

• 5+ years of experience applying ML or data science to real business problems at scale 

• Master’s degree (or higher) and 4+ years of experience in CS, CE, ML, or a related field 

• Strong CS fundamentals and ability to design efficient algorithms and production systems 

• Experience with ML approaches used in large-scale data problems (e.g., regression, classification, tree-based methods, embeddings, sequence models, or basic NLP) 

• Strong intuition for defining KPIs, objective functions, and evaluation frameworks for ML-driven systems 

PREFERRED QUALIFICATIONS 

• Knowledge of programming languages such as Python, Scala/Java, C/C++, or similar 

• Experience working with large-scale data platforms (Spark, Presto/Trino, feature stores, data lakes, etc.) 

• Experience building or integrating with LLM/Gen-AI pipelines (prompting, evaluation, retrieval, safety) is a plus 

• Prior publications, patents, or open-source contributions are a plus 

About the role  

Our Search Platform sits at the heart of the Roku experience, powering voice, text, and visual discovery across 100M+ active accounts and every Roku-powered device worldwide.
 We own the entire stack —from ingesting & enriching a multi-million-title knowledge graph, to low-latency retrieval services and large-scale machine-learning systems that personalize results in real time. Our work doesn’t just help users find shows; it drives core product surfaces (home-screen rows, browse hubs, Roku Voice, mobile app search) and fuels partner monetization. If you enjoy turning cutting-edge research into products used billions of times a day, you’ll thrive here.

Roku’s footprint has more than quadrupled in the past five years, and user expectations have leaped just as fast—think LLM-based query understanding, vector-DB retrieval, on-device models, and multimodal search (voice, text, image). We’re now rebuilding our relevance stack for the next decade, blending classic IR with generative-AI techniques. You will be a technical leader spearheading that transformation. 

What you'll be doing 

• Apply state of the art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations to make our users more delighted and engaged on the platform 
• Run online AB tests and analyze them against the critical business KPIs 
• Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications 
• Nurture our ML ecosystem to make it withstand scale, developer velocity and future business shifts 
• Provide technical leadership to drive technical and ML roadmap for search ranking and monetization 
• Help recruiting new engineers. Interview, train, and mentor new team members 
  
  We're excited if you have 
  
  
• 7+ years of experience (or PhD with 5 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation or search or ads 
• Strong CS fundamentals. Should be able covert ideas to code with ease 
• Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models. Familiarity with modern NLP stack and multi-modal representation learning is a plus 
• We'd love to see that you've worked with big data systems (Spark, S3, and Airflow) and can program (Java, Scala, or Python)  
• Good understanding of system architecture 
• Experience in big data technologies and streaming architecture, data pipelines, etc. 
• MS in Computer Science, Statistics, or related field, but a Ph.D. in CS or related fields is preferred 
  
• AI literacy and curiosity.You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it. 

#LI-AK1

About the team

A highly scalable, highly available, real-time advertising platform is critical to support and grow Roku's rapidly expanding ad business. It is the mission of the Ad Engineering Team to build this platform. We are hiring a Senior Machine Learning Engineer, Advertising Platform, to be a vital part of this mission. If you bring extensive experience building complex systems using Machine Learning and Data Science, love great technology at scale, enjoy mentoring, jumping in, and figuring things out in any system, this role is for you!

The Ad Serving team, based in Bangalore, is responsible for ensuring that ads on the Roku platform are relevant and of good quality, leading to better outcomes for advertisers and providing a great experience for our viewers. Dealing with millions of ad requests in a day, we need to have best in class ML driven systems to improve the way we serve ads in multiple countries and languages.  

About the role

In this role, you will build and develop ML models to solve for content understanding aspects of Ads. These models rely on the visual, audio and textual content of ads, across multiple languages. This includes developing computer vision and machine learning models/methods such as deep learning models, generative AI solutions, large language models (LLMs) and vision language models (VLMs). You will work with software engineers and other ML engineers to identify, build, train and productionize these models to improve brand safety, increase revenue opportunities and help with moderation and generation of ad creatives in general.

What you will be doing

• Develop scalable and effective machine-learning models and optimization strategies to solve business problems related to Ads
• Run regular A/B experiments, gather data, and perform statistical analysis
• Work closely with software engineers and other ML engineers to deliver end-to-end solutions into production
• Improve the scalability, efficiency and automation of ML driven ad serving systems, model training, deployment and serving
• Partner with senior stakeholders to plan and drive the ML strategy for Ad Serving

We're excited if you have

• 6+ years of building models for business application experience
• Master's degree ( or higher) and 4+ years of CS, CE, ML or related field experience
• Strong CS fundamentals. Should be able to write an algorithm with ease.
• Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
• Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, sequence-based, and NLP approaches like W2V or Bert
• Can brainstorm and identify the right KPIs and objective functions. 
• Knowledge of programming languages such as C/C++, Python, Java or Perl (preferred)
•  Have publications at top-tier peer-reviewed conferences or journals (preferred)
• AI growth mindset / AI Literacy

About Us (Ensono)

Ensono is an expert technology adviser and managed service provider. As a relentless ally, we accelerate clients’ digital transformation to achieve business outcomes that stand to last. Our dedicated team helps organizations optimize today’s systems across any hybrid environment with services such as consulting, mainframe and application modernization, public cloud migration and cloud-native development. With certified experts in AWS, Azure and Google Cloud and recognized as Microsoft Datacenter Transformation Partner of the Year, Ensono has over 3500+ associates globally and is headquartered in greater Chicago.

We care about your success, offering comprehensive strategic and managed services for mission-critical applications. Our Advisory and Consulting services can help upfront with an application strategy or find the right places for your applications – whether it’s public, multi or hybrid cloud, or mainframe. And because we span across all mission-critical platforms, we can meet you wherever you are in your digital transformation journey, with 24/7 support when you need it. We are your relentless ally, flexing with you when challenges emerge so you don’t feel stuck in place. With cross-platform certifications and decades of experience, our technology experts have become an extension of your team so you’re continuously innovating – doing more with less while remaining secure. And that’s just the beginning.

Job Description: Business Intelligence Manager

Position Summary

The Business Intelligence (BI) Manager is responsible for leading the strategy, development, and operational excellence of enterprise analytics, reporting, and AI-enabled insights. This role oversees BI platforms, data visualization, and analytical solutions—including the responsible application of AI and advanced analytics—to enable data-driven decision-making across the organization. The BI Manager partners with business leaders, data engineering, AI governance, and security teams to ensure insights are accurate, explainable, secure, and aligned with business priorities.

Key Responsibilities

Strategy & Leadership

• Define and execute the enterprise BI and analytics strategy, including AI-enabled insights, aligned to business objectives and data governance standards
• Lead, mentor, and develop a team of BI developers, analysts, and analytics engineers
• Establish prioritization frameworks for analytics and AI-driven use cases
• Serve as a trusted advisor to business and executive stakeholders on analytics and AI capabilities

Analytics, AI & Insights Delivery

• Oversee the design, development, and maintenance of dashboards, reports, predictive models, and AI-assisted analytics products
• Enable the use of AI for trend analysis, forecasting, anomaly detection, and insight generation using governed enterprise data
• Ensure consistent semantic models, metrics definitions, and explainable outputs across BI and AI solutions
• Partner with data science and data engineering teams to operationalize AI outputs into BI platforms and business workflows
• Drive adoption of AI-assisted self-service analytics while maintaining data quality, lineage, and control

Platforms & Technology

• Own BI and analytics platforms (e.g., Power BI, Tableau, Looker) and their integration with AI and cloud data platforms
• Support AI-enabled features such as natural language query, automated insights, and embedded copilots where appropriate
• Define standards for dashboard design, AI explainability, usability, accessibility, and performance
• Lead platform optimization, licensing strategy, and cost management across BI and AI tooling

AI Governance, Security & Responsible Use

• Ensure AI use of data complies with enterprise AI governance, security, privacy, and ethical standards
• Partner with security, risk, and compliance teams to enforce access controls, sensitivity labeling, and usage monitoring
• Support model transparency, bias awareness, and auditability for AI-derived insights
• Maintain documentation for AI use cases, assumptions, and limitations

Data Governance & Quality

• Enforce data governance, certification, and lifecycle management for BI and AI assets
• Establish data quality and AI output validation processes
• Maintain business glossaries, metric definitions, and AI-enabled analytics documentation
• Support audit, compliance, and regulatory requirements related to analytics and AI

Stakeholder Engagement & Value Realization

• Translate business questions into analytics and AI use cases with measurable outcomes
• Enable business teams through training on BI tools, AI-assisted analytics, and responsible usage
• Measure and report on analytics and AI value realization, adoption, and business impact

Required Qualifications

• Bachelor’s degree in information systems, Computer Science, Data Analytics, Business, or related field
• 7–10 years of experience in business intelligence, analytics, or data platforms
• 3+ years of experience leading BI or analytics teams
• Strong expertise in BI platforms (Power BI preferred) and enterprise data architectures
• Demonstrated understanding of AI-assisted analytics and advanced analytical techniques
• Proven experience partnering with senior business stakeholders
• Strong understanding of data governance, security, and compliance principles

Preferred Qualifications

• Experience in managed services, consulting, or multi-client environments
• Familiarity with cloud data platforms (e.g., Snowflake, Azure Synapse, BigQuery)
• Exposure to AI platforms, embedded analytics, or analytics copilots
• Knowledge of data cataloging, lineage, and governance tools (e.g., Microsoft Purview or equivalents)
• Experience operationalizing AI insights within enterprise reporting environments

Key Competencies

• Strategic analytics and AI thinking with operational execution
• People leadership and talent development
• Executive communication and stakeholder influence
• Data ethics, governance, and risk awareness
• Continuous improvement and innovation mindset

Success Measures

• Increased adoption of BI and AI-enabled insights across the enterprise
• Consistent, trusted, and explainable KPIs and AI outputs
• Improved time-to-insight and decision quality
• Strong governance, security, and audit outcomes
• Demonstrated business value from analytics and AI initiatives

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to caste, colour, creed, religion, gender, gender identity, sexual orientation, age, disability, HIV status, or any other status protected by law. Candidates with disabilities who require accommodations during the recruitment process are encouraged to contact our Talent Acquisition team to place a request.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Fee Insights builds fee explainability experiences that help merchants and internal teams understand what they're paying and why. We tackle this through agentic systems that provide natural language explanations grounded in canonical fee data, self-serve tooling, and also experiences that help users reconcile and understand complex pricing at scale.

Fee transparency and explainability are critical to merchant trust and satisfaction. As Stripe's product portfolio and pricing complexity has grown, helping users understand their fees—and how they align with their contract and product usage—has become increasingly important. We're solving fundamental questions around fee transparency, building the foundations that will scale across Stripe's merchant base.

What you’ll do

As a Software Engineer on Fee Insights, you'll work on crafting billing-related experiences for both internal teams and external merchants. You'll partner closely with product teams to build reporting, dashboards, insights, and guided user journeys that help users interact with pricing and understand fees. You’ll be navigating one of Stripe's most complex domains, gaining deep end-to-end understanding of how Stripe works—from payments to pricing to billing.

Responsibilities

• Building and iterating on fee explainability experiences that empower users to find answers independently
• Developing agentic systems with strong accuracy guarantees—building evaluation frameworks and ensuring reliability at scale
• Creating performant data aggregations and optimizations to handle complex pricing scenarios
• Working across the stack: backend services, frontend experiences, data pipelines, and AI agents
• Collaborating with stakeholders across engineering, product, operations, finance, accounting, and sales
• Independently identifying solutions to user pain points and executing against roadmaps
• Mentoring junior engineers and raising the technical bar for the team

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of professional experience in a software development role
• Strong coding skills in any programming language
• Ability to drive and lead large-scale initiatives that solve critical business challenges
• Strong collaboration skills across teams and workstreams
• Track record of developing and delivering high-quality software using industry best practices
• Ability to make effective tradeoffs that balance business priorities, user experience, and technical sustainability

About the role

Hiring is one of the most consequential decisions a company makes. 3,000+ enterprises rely on HackerRank to get it right. We are now reinventing how that works for the agentic era. The ML systems that power this platform are not auxiliary features. They are the product.

Open Problems

The agentic era is reshaping every layer of the hiring stack. These are some of the core problems you'll be working across, none of them fully solved.

• Chakra: Building an autonomous AI interviewer that conducts, adapts to, and evaluates technical interviews end to end.
• Integrity: Detecting fraud and suspicious behavior across multiple signal types. The ways candidates game assessments change frequently, and the models need to keep up.
• Evaluation: Measuring technical skill in a world where AI writes the code. The old proxies no longer hold and the new ones have not been defined yet.

Your focus will shift across these depending on where the highest-leverage work is at any given time.

What you will do

• Design and ship production ML systems across Chakra, integrity, and evaluation domains.
• Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration.
• Build evaluation infrastructure and benchmarking pipelines that reliably measure model quality before and after deployment.
• Define the architecture and production bar for different signal categories from scratch. 
• Mentor and support junior ML engineers, helping shape their technical thinking and raise the quality bar across the team.
• Establish ML best practices for the team: monitoring, model feedback loops, and quality standards.

Who you are

• 4+ years building and shipping ML systems that run in production at scale.
• Systems thinking comes naturally. Model accuracy, data pipelines, serving infrastructure, and customer outcomes are one problem, not four.
• Evaluation methodology matters as much as model performance. A metric measured wrong is worse than no metric.
• Proficient in Python, with practical experience building data pipelines and deploying models to production.

Even better if you have

• Experience with multimodal systems: vision, NLP, audio, or behavioral signal pipelines.
• LLM experience: fine-tuning, RLHF, or multi-turn agentic systems.
• Background in adversarial ML, fraud detection, or anomaly detection.
• Publications or open-source contributions in detection, robustness, or evaluation methodology.

You will thrive here if

• Messy, undefined problems are more interesting to you than optimizing within clean ones.
• Ambiguity energizes you, especially when the right framing is itself part of the work.
• Direct access to leadership, fast feedback loops, and genuinely unsolved problems is what you are looking for.
• Defining what a system should be is more compelling than maintaining what already exists. 

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

About Inizio Ignite

We are Inizio Ignite, the global advisory partner for health and life sciences encompassing connected expertise across Research Partnership, Putnam, STEM, and Vynamic. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – helping healthcare leaders shape strategy and drive meaningful change. 

About the Role

We are seeking an experienced Data Science Manager to join our team at Inizio Ignite. The ideal candidate will bring deep machine learning expertise, strong GenAI and cloud competencies, and hands-on experience delivering analytical solutions that drive meaningful business impact for life sciences clients.

This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.

What you'll be doing

Leadership & Delivery

• Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.
• Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.
• Translate business problems into analytical frameworks and ensure high-quality, timely project execution.
• Drive adoption of AI/ML capabilities across client engagements and internal initiatives.

Technical Responsibilities

• Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.
• Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).
• Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.
• Ensure adherence to model governance, compliance, and responsible AI frameworks.

What you'll need

• Extensive experience in data science or advanced analytics roles, with at least 2–3 years in a leadership or managerial capacity.
• Ideally prior experience in pharmaceutical, biotech, or healthcare consulting is mandatory.
• Strong expertise in machine learning, NLP, deep learning, and GenAI (LLMs, prompt engineering, RAG, fine-tuning, embeddings).
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP; exposure to MLOps frameworks preferred.
• Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).
• Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.
• Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.
• Experience building GenAI solutions in production environments

Our Pledge

At Inizio, we value inclusivity, recognize the power of diversity, and inspire the next generation of change-makers. We are an equal opportunities employer and are committed to creating a dynamic work environment that values diversity, equity, and inclusion. We welcome all applications regardless of race, color, religion, gender identity, age, national origin, marital status, veteran status, genetic information, sexual orientation, or disability.

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly align with every qualification, we encourage you to apply anyway.

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta seeks a skilled Staff Full Stack Engineer with expertise in NetSuite and/or  Oracle Fusion Cloud Applications. As part of our Business Technology team, you will be responsible for developing and optimizing full-stack solutions, including custom scripts, workflows, integrations, and system enhancements for both NetSuite and Oracle Fusion to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We’d love to hear from you!

Job Duties and Responsibilities

• Design, develop, and maintain full-stack solutions for Finance Tech stack like NetSuite, Coupa and Oracle Fusion Cloud Applications etc., using any of the full-stack applications like Node Js/React
• Develop and maintain robust off-platform integration scripts using Python & LangChain to manage data transfer and interactions between NetSuite (via SuiteTalk or RESTlets) and AI Platforms
• Architect and implement scalable, secure, and cost-efficient cloud-native solutions on AWS for RAG, MCP, and Agentic AI (LangGraph) 
• Closely work with the BT Product Manager to design, develop, test, implement & support system solutions primarily in Finance Technology
• Provide technical consultation, best practices, and problem resolution for AI and Agentic AI for the Finance tech stack NetSuite, Oracle Fusion, and associated integrated systems
• Support & resolve production issues across the full application stack
• Develop and maintain integrations with third-party applications via REST/SOAP APIs
• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases and explore similar capabilities in Oracle Fusion

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Deep hands-on experience with AWS solutioning, including designing and deploying production applications using core services such as AWS EC2, AWS Lambda, Amazon S3, Amazon RDS, and API Gateway. Familiarity with Infrastructure as Code (IaC) tools like CloudFormation or Terraform is essential.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions
• Strong understanding of Finance Business processes (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities
• Working Experience on the MCP and familiar with SaaS MCP connectors, like NetSuite MCP or similar
• Working experience with foundational AI services, with a desire to use a unified platform like AWS Bedrock for Generative AI development and deployment
• Nice to have some core Amazon Machine Learning (ML) services, specifically AWS SageMaker (for building, training, and deploying custom ML models), AWS Comprehend (for natural language processing and text analytics), and  Retrieval Augmented Generation (RAG)

Education and Certifications

• A Bachelor’s degree in Computer Science, Information Systems, or equivalent years of industry experience
• AWS cloud Certification or any ERP foundation certificate is a plus

#P16568_3435773
#LI_Hybrid

The Role

We are currently seeking a Staff Software Engineer, Infrastructure to join the AI Platform team that powers seamless insights and interaction through natural language and data intelligence across our AI products.

As a Staff Software Engineer, you’ll architect, build, and operate the backend and platform systems that power AI Platform. You’ll work across service design, distributed systems, cloud infrastructure, event-driven processing, observability, CI/CD, and production reliability, helping shape the technical direction of a platform that supports scalable, client-facing AI experiences.

This role requires a strong software engineering foundation combined with deep infrastructure and systems thinking. We are looking for an engineer who can write high-quality production code, make sound architectural tradeoffs, and own platform capabilities end-to-end — not someone focused only on scripting, cloud configuration, or infrastructure tooling in isolation.

You will collaborate closely with frontend, product, and AI/ML engineers to deliver reliable, secure, and scalable systems that align with Addepar’s standards of performance, resilience, and trust.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

• Design, build, and operate backend services and infrastructure that power AI Platform products.
• Write high-quality production code for platform and service layers, with strong emphasis on maintainability, reliability, and performance.
• Architect and evolve distributed systems that support AI Platform capabilities such as real-time interactions, asynchronous processing, and secure data workflows.
• Build and extend cloud-native infrastructure across core services, networking, storage, identity, and observability layers.
• Design and maintain infrastructure as code using Terraform, including reusable modules, environment management, and drift-safe workflows.
• Build and operate Kubernetes/EKS-based services, including deployment strategies, health checks, scaling configuration, and containerization workflows.
• Design and improve CI/CD pipelines, release workflows, and engineering productivity systems.
• Build and maintain asynchronous and event-driven systems using queues, RPC/service communication, and resilient failure-handling patterns.
• Design and evolve relational and NoSQL data models, including schema design, migrations, replication, and access patterns.
• Build and maintain observability across metrics, logs, tracing, dashboards, and alerting.
• Apply secure-by-default engineering practices across IAM, secrets, encryption, network isolation, and production operations.
• Mentor engineers through code review, design review, incident reviews, and technical guidance.
• Drive technical decisions that improve platform reliability, scalability, developer productivity, and long-term system health.

Who You Are

• Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
• At least 8+ years of professional software engineering experience, including significant experience in backend, infrastructure OR platform oriented work.
• Strong proficiency in at least one production backend language such as Python, Go, OR Java and the ability to work effectively across a polyglot environment.
• Strong software engineering fundamentals, including system design, debugging, code quality, testing, and operational ownership.
• Deep hands-on experience with cloud infrastructure in production environments.
• Strong experience with infrastructure-as-code workflows such as Terraform or equivalent tools.
• Experience with Kubernetes/EKS, Docker, and modern deployment practices.
• Experience designing or extending CI/CD pipelines in production environments.
• Experience with distributed systems, microservice communication, message queues, asynchronous processing, and failure handling.
• Experience with both relational and NoSQL database design in production systems.
• Strong observability and production-debugging skills.
• Strong communication, collaboration, and mentoring skills.
• Ability to operate as a software engineer first: we are not looking for someone who is only strong in scripting, cloud configuration, or infrastructure tooling without corresponding depth in production software engineering.

Bonus

• Experience with AI/ML platform tooling such as Databricks, Spark, MLflow, or model-serving systems.
• Experience with real-time streaming or WebSocket-based systems at scale.
• Experience with multi-region architectures, data residency, or failover design.
• Experience in fintech or other highly regulated environments.
• Experience optimizing platform cost, performance, and reliability tradeoffs at scale.

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest in the USA and has employees who live across the country. As we expand our global footprint with a new presence in Hyderabad, India, we’re building a world-class team to help us scale this mission and Clinical Intelligence and AI Evaluation is at the heart of everything we do. This job requires daily onsite work at our headquarters in Hyderabad, India.

Who We Need

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

This Opportunity

This Clinical Data Analyst position is a high impact, intellectually challenging role that requires a diverse set of analytical and technical skills. It provides unique opportunities for growth using an unprecedented amount of high-quality real-word Electronic Health Record (EHR) data and clinical notes data and become a nexus of healthcare and technology. You will be solving meaningful and consequential problems in healthcare using an EHR and clinical notes database of 120 million US patients (and growing!) and help drive insights that can ultimately improve and impact on patient care. This position will report to our Director of Clinical Intelligence and AI Evaluation team and support end-to-end evaluation, extraction, execution and delivery of custom concepts from clinical notes and EHR data to help our customers dive deeply into complex research questions related to human health and generate data-driven insights that support impactful scientific decisions.

Responsibilities

· Use technical skills to scope out clinical informatics data analyses requests from both internal and external customers, produce studies and results within an agreed deadline.

· Communicate on the status of various projects and collaborate with multidisciplinary stakeholders to ensure that clinical data projects are successfully executed and delivered.

· Excel in providing technical analytics support as well as directly working with internal stakeholders to troubleshoot any data analyses. Work with customers to achieve their goals, teaching them how to wrangle and analyze data using SQL, R and Python on real-world data to address their empirical questions.

· Write Databricks SQL queries to extract, analyze and interpret clinical concepts from clinical notes per customer requests.

· Create dashboards, data visualizations, and data tools to support data-driven decision making.

· Create enablement materials and studies as the Truveta platform evolves to help new researchers to increase our capabilities.

· Collaborate closely with other Truveta teams to conduct investigations of data sources to demonstrate veracity to current internal and external customers.

· Deliver feedback to internal teams based on customer requests to inform Truveta’s product roadmap.

Required Skills

· Graduate or Masters level educational degree in clinical research, data analysis, data science, clinical informatics, health information management or related fields.

· 3+ years of demonstrated experience conducting analyses using large healthcare datasets (e.g., electronic health records, clinical notes or other real-world data sources consisting of millions of patients' data.).

· 3+ years of demonstrated experience working with customers or research teams to translate their asks into executable analytical code, rigorous quality analytical datasets, deliver high quality research analyses.

· Strong proficiency in SQL, at least one statistical programming language (R or Python), familiar with Spark bigdata analytics environments, for data wrangling, analysis, and reproducible research workflows.

· Strong hands-on problem-solving skills, troubleshoot and identify data or methodological issues early and communicate them effectively. Have ownership, accountability and reliability mindset.

· Excellent written and verbal communication skills, including the ability to clearly explain analytical approaches and findings to technical and non-technical stakeholders.

· Ability to learn and adapt quickly in a dynamic start-up environment and a good team-player.

· Willingness to learn new analytical tools, programming languages, and proprietary platforms used to analyze real-world data.

Preferred Qualifications

These qualifications are preferred but not required, please do not let them stop you from applying for this role. You will likely get the opportunity to learn how to do these more advanced analyses if you don’t already have experience with them.

· Spark/PySpark, Databricks experience

· Experience working with unstructured clinical data or natural language processing outputs

· Regex query writing experience

· Experience building cohort definitions or eligibility criteria for research studies

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. We are expanding our global footprint. Join us as we build an amazing company together.

We Offer:

· Interesting and meaningful work for every career stage

· Great benefits package

· Comprehensive benefits with strong medical, dental and vision insurance plans

· Professional development & training opportunities for continuous learning

· Work/life autonomy via flexible work hours and flexible paid time off

· Generous parental leave

· Regular team activities (virtual and in-person as soon as we are able)

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude people from some sections, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements

• Design, deploy, and scale large-scale ML and data processing pipelines across cloud infrastructure.
• Build systems to ingest, process, and serve 250,000+ hours of multimodal data (video, audio, metadata).
• Architect and optimize GPU-based compute environments (e.g., NVIDIA Tesla clusters) for distributed training and inference.
• Develop high-throughput backend systems for video ingestion from desktop and mobile platforms.
• Implement distributed processing workflows, including job scheduling, fault tolerance, and resource allocation.
• Design and build human-in-the-loop and automated annotation systems to ensure data quality and scalability.
• Translate ML and multimodal research into scalable, production-grade cloud architectures.
• Optimize pipelines for performance, reliability, and cost efficiency across compute, storage, and networking layers.
• Collaborate with ML, data, and engineering teams to deliver end-to-end data workflows.

• 5+ years of experience in data engineering, ML pipelines, or distributed systems.
• Strong experience building scalable data pipelines for large datasets (video/audio preferred).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Experience working with GPU-based environments and distributed computing.
• Strong programming skills in Python, Scala, or similar languages.
• Experience with data processing frameworks (Spark, Ray, Kafka, Airflow, or similar).
• Understanding of ML workflows, training pipelines, and inference systems.
• Experience designing fault-tolerant, high-availability systems.
• Strong knowledge of data storage systems (data lakes, object storage, distributed file systems).
• Ability to handle high-throughput, large-scale data ingestion and processing.

• Experience with multimodal AI (video, audio, NLP) systems.
• Familiarity with annotation tools and data labeling workflows.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Knowledge of cost optimization strategies for large-scale cloud workloads.

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.  

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. 

Role Overview

We are hiring a Prompt Engineer with a strong clinical informatics background to build and optimize AI prompts for healthcare and clinical data applications. This role requires hands-on clinical understanding, experience working with real clinical data, experience writing prompts for AI models, and the ability to align LLM prompts with underlying clinical data models.

You will work closely with clinicians, data engineers, and AI teams to translate clinical questions and workflows into accurate, safe, and scalable AI interactions.

Key Responsibilities

• Design, test, and optimize prompts for LLM-based clinical use cases such as:
• Cohort identification
• Clinical question answering
• Concept extraction
• Clinical code mapping
• Translate clinical requirements into structured prompts aligned with clinical data schemas
• Collaborate with data engineers to understand how diagnoses, labs, medications, encounters, and outcomes are modeled
• Evaluate AI outputs for clinical accuracy, relevance, bias, and safety
• Apply healthcare data standards (FHIR, SNOMED CT, LOINC, RxNorm, ICD-10-CM) within prompt logic and validation
• Create prompt evaluation criteria and quality benchmarks
• Document reusable prompt patterns and best practices
• Continuously improve prompts based on model behavior and user feedback.

Required Qualifications

• 2–5 years of experience in clinical informatics, healthcare analytics, or health IT
• Clinical background required, such as:
• Nursing, pharmacy, medicine, public health, or clinical informatics
• OR hands-on experience working with clinical workflows or EHR data
• Strong understanding of clinical data modeling, including representation of:
• Diagnoses, procedures, medications
• Laboratory results and vitals
• Encounters and outcomes
• Practical experience with healthcare data standards:
• FHIR
• SNOMED CT
• LOINC
• RxNorm
• ICD-10-CM
• Hands-on experience with LLMs and prompt engineering for applied or production use cases
• Ability to critically evaluate AI outputs for correctness and clinical safety
• Strong analytical, documentation, and communication skills

Preferred

• Experience with clinical NLP or unstructured clinical text
• Familiarity with EHR systems or clinical data repositories
• Working knowledge of Python for prompt testing or evaluation
• Working knowledge of SQL for exploring clinical datasets
• Experience combining structured and unstructured healthcare data
• Prior work on healthcare AI, decision support, or analytics platforms

Smartsheet is establishing a new Enterprise Insights & Intelligence team to centralize ownership of corporate metrics, analytics governance, and self-serve data enablement. This is a foundational hire — you will help build this function from the ground up, with direct visibility to senior leadership and the opportunity to shape how the entire organisation consumes and trusts its data.

We are looking for a Senior Business Intelligence Engineer who can operate across three strategic pillars: automating and governing corporate executive reporting, standardising metrics and reporting practices at scale, and enabling self-serve and AI-powered data solutions. Day to day, this means you could be building an automated executive scorecard, codifying metric definitions into a governed semantic layer, standing up an AI agent that lets business users query trusted data in natural language, or leading enablement sessions on our analytics platforms. The thread connecting all of it is ensuring that Smartsheet's data is trusted, consistent, accessible, and ready for both human and AI consumption.

This is not a traditional reporting or data science role. You will work across dbt, MetricFlow, Snowflake, and Databricks to build the governed data layer that underpins everything — from board-level scorecards to LLM-powered insights to self-serve dashboards.

You Will

• Design, build, and maintain governed metric models — standardised, reusable definitions of business KPIs that dashboards, reports, and AI agents all query from a single source of truth
• Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting
• Conduct deep dives on key KPIs and company goals, surfacing actionable insights and translating short- and long-term business priorities into data-driven recommendations shared via reviews and async updates
• Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets
• Build AI agent integrations (MCP servers, skills, subagents) that allow tools like Claude and Snowflake Cortex to query enterprise data through the semantic layer with metric-correct SQL
• Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms
• Partner with Product, Engineering, Finance, GTM, and Customer Success to align metric definitions and data sources cross-functionally
• Translate qualitative UX signals and customer feedback into measurable data pipelines

You Have

• Bachelor's degree (B.Tech / B.E. / B.Sc.) in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
• 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role
• Experience with KPI design and insight generation — ability to define meaningful metrics, analyse trends, identify anomalies, and communicate findings that drive business decisions
• Familiarity with dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models; hands-on experience is a plus but not required
• Deep SQL expertise with experience working in cloud data platforms such as Snowflake and/or Databricks
• Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption
• Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models
• Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar)
• Strong cross-functional collaboration skills and excellent async communication across time zones (IST / US Pacific overlap expected)
• A proactive, ownership-driven mindset — comfortable building new processes and standards in a greenfield environment

Preferred Qualifications

• Experience building AI agent skills, subagents, or MCP server integrations for LLMs
• Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows
• Software engineering experience (Python, JavaScript/TypeScript) with the ability to contribute to application-level instrumentation code
• Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.)
• Familiarity with metric governance frameworks, data catalogues, or data quality tooling
• Prior experience working in a SaaS or enterprise software environment

Position Summary:

Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.

The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.

The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.

Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)

1. AI / ML Model Development & Optimization

• Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
• Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
• Optimize model performance across accuracy, latency, scalability, and cost dimensions.
• Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
• Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.

1. Production Deployment & MLOps

• Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
• Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
• Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
• Troubleshoot and resolve AI/ML engineering issues across development and production environments.

1. Cross-Functional Collaboration & Integration

• Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
• Translate product requirements and use cases into technical architectures and model designs.
• Support integration of AI capabilities into customer-facing products and internal platforms.
• Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.

1. Data & Domain Application

• Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
• Ensure responsible handling, transformation, and validation of data used for model training and inference.
• Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.

1. Technical Excellence & Continuous Improvement

• Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
• Contribute to internal best practices, standards, and reusable components for AI/ML development.
• Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
• Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.

Qualifications:

BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field

Minimum Required:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
• Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
• Deep hands-on experience with machine learning, deep learning, and natural language processing.
• Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
• Working knowledge of data preprocessing, feature engineering, and model validation practices.
• Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Preferred:

• Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
• Hands-on experience with MLOps frameworks and monitoring strategies.
• Experience integrating AI models into SaaS products or productized services.
• Familiarity with distributed systems, APIs, and modern software engineering practices.
• Exposure to enterprise AI governance, security, or compliance considerations.

Competencies:

• Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
• Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
• Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
• Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
• Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
• Solutions oriented: must be able to display resourcefulness and confidence under pressure
• Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.

Position Summary:

Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.

The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.

The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.

Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)

1. AI / ML Model Development & Optimization

• Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
• Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
• Optimize model performance across accuracy, latency, scalability, and cost dimensions.
• Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
• Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.

1. Production Deployment & MLOps

• Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
• Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
• Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
• Troubleshoot and resolve AI/ML engineering issues across development and production environments.

1. Cross-Functional Collaboration & Integration

• Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
• Translate product requirements and use cases into technical architectures and model designs.
• Support integration of AI capabilities into customer-facing products and internal platforms.
• Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.

1. Data & Domain Application

• Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
• Ensure responsible handling, transformation, and validation of data used for model training and inference.
• Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.

1. Technical Excellence & Continuous Improvement

• Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
• Contribute to internal best practices, standards, and reusable components for AI/ML development.
• Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
• Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.

Qualifications:

BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field

Minimum Required:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
• Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
• Deep hands-on experience with machine learning, deep learning, and natural language processing.
• Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
• Working knowledge of data preprocessing, feature engineering, and model validation practices.
• Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Preferred:

• Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
• Hands-on experience with MLOps frameworks and monitoring strategies.
• Experience integrating AI models into SaaS products or productized services.
• Familiarity with distributed systems, APIs, and modern software engineering practices.
• Exposure to enterprise AI governance, security, or compliance considerations.

Competencies:

• Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
• Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
• Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
• Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
• Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
• Solutions oriented: must be able to display resourcefulness and confidence under pressure
• Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.

Cialfo is a leading platform connecting students, higher education institutions, and counselors through technology-driven solutions. Launched in 2017 with a mission to make education accessible to 100 million students, Cialfo provides a range of mobile and web solutions to students, K-12 institutions, and higher education institutions. We’re one of the fastest-growing tech startups in the region, consistently charting new heights!

This position is with Cialfo and BridgeU, one of the brands under Manifest Global, which also includes Explore and Kaaiser. 

About This Role

We are looking for a Senior Marketing Manager to own both go-to-market strategy and pipeline generation for the Cialfo and BridgeU K12 platform. This is a high-ownership, hands-on role that combines the strategic depth of a Product Marketing Lead with the execution rigour of a Demand Generation Lead.

You will own product positioning, messaging, competitive intelligence, and voice of the customer — while simultaneously driving pipeline across web, digital, lifecycle, events, social, and ABM. You will be the strategic link between what we build and how the market receives it, and you will own the campaign engine that converts that positioning into revenue.

You will use AI tools natively across the entire marketing lifecycle — from audience research and brief generation through to creative production, performance analysis, and reporting — and you will operate as a true partner to the K12 Sales team, owning MQL quality, the handoff process, and pipeline SLAs.

This role is based in Delhi, India and reports into the Head of Marketing, K12. This is an Individual Contributor role to begin with, with an opportunity to build and scale a team as the business grows.

What You Will Be Doing

Product Positioning & Messaging

• Build and own positioning, naming, and messaging frameworks for K12 product launches.
• Develop and maintain ICP definitions and buyer personas across K12 audience segments — schools, counselors, students, and parents — across different markets.
• Ensure messaging is regionally calibrated and relevant; what lands in LATAM needs a different frame in India or the Middle East.
• Partner with UX to align in-product messaging and onboarding flows.

Go-to-Market Execution

• Lead end-to-end GTM planning — from positioning through channel execution to adoption measurement.
• Drive feature adoption through in-product channels (email, push, in-app) coordinated with lifecycle triggers.
• Train internal stakeholders on every launch — Sales, CX, and leadership as a core GTM deliverable.
• Use AI tools to accelerate GTM output: content production, personalisation, testing, and reporting.

Pipeline Ownership & Demand Generation

• Own pipeline generation across all channels — digital, email, lifecycle, social, events, and ABM — fully attributed to revenue.
• Drive MQL volume and conversion rates across the K12 websites (Cialfo and BridgeU) and campaign channels.
• Manage pipeline efficiency from first touch to SQL handoff with clear SLA accountability to the Sales team.
• Set and track demand gen KPIs: MQL volume, cost per MQL, MQL-to-SQL conversion rate, pipeline contribution, and channel ROI.

Full-Funnel Campaign Execution

• Design and execute integrated campaigns across web, lifecycle email, social, events, content, and ABM.
• Own the campaign calendar, prioritising by pipeline impact and coordinating across channels for consistent messaging and timing.
• Manage external vendors and hold them accountable to performance targets, briefs, and delivery timelines.
• Build scalable campaign processes that enable faster execution and consistent cross-channel measurement.
• Run hypothesis-driven A/B tests across every channel — landing pages, email subject lines, ad creative, CTAs — and act on results fast.

Sales & CX Enablement

• Build and own the K12 enablement library: pitch decks, one-pagers, objection handling guides, battlecards, and demo talk tracks.
• Run regular enablement sessions with global Sales and CX teams.
• Partner with CX on customer success stories and reference content tied to specific product use cases.

Lifecycle & Email Marketing

• Own the full lifecycle marketing programme from first touch nurture through to re-engagement across the K12 audience of school leaders, administrators, and counselors.
• Design and manage automated workflows in HubSpot that move leads through the funnel and surface high-intent signals for Sales.
• Segment audiences by persona, behaviour, and funnel stage to deliver relevant messaging at the right moment.
• Monitor and improve lifecycle metrics: open rates, click-through rates, nurture-to-MQL conversion, and unsubscribe rates.

Voice of the Customer (VoC)

• Own Cialfo's structured VoC program for K12 — regular interviews and feedback loops with schools, counselors, and students across key markets.
• Synthesise qualitative and quantitative signals into actionable insights for Product, UX, and leadership.
• Build and maintain a VoC repository so customer language, pain points, and unmet needs are systematically captured and accessible.
• Run advisory panels or user research sprints in partnership with Product to inform the roadmap.

Win/Loss & Competitive Intelligence

• Own the win/loss program — conduct regular interviews with won and lost opportunities, synthesise findings, and present to Product, Sales, and leadership quarterly.
• Build and maintain competitive intelligence: monitor the landscape, develop battlecards, and keep Sales and CX equipped to win.
• Feed competitive and customer insights back into positioning and product feedback loops.

Social Demand Generation

• Run social as a demand gen channel — not just brand awareness — with a focus on generating engagement, traffic, and leads from LinkedIn and other relevant platforms.
• Build and manage social campaigns targeting school decision-makers across global markets.
• Collaborate with content and brand to ensure social creative is optimised for conversion, not just reach.

Website & Conversion Optimisation

• Own the Cialfo K12 website end to end — performance, conversion optimisation, lead capture, and user experience.
• Implement and monitor UTM tracking, campaign attribution, and accurate data capture across all entry points.
• Run continuous experiments on landing pages, forms, and conversion flows to improve MQL volume.

Sales Partnership & ABM

• Operate as a genuine partner to the K12 Sales org — attend pipeline reviews, understand deal velocity, and align demand gen programmes to Sales priorities.
• Own the MQL-to-SQL handoff process: lead scoring, SLA compliance, follow-up timelines, and lead quality feedback loops.
• Build and execute Account-Based Marketing programmes targeting priority school accounts across key markets.

AI-Powered Marketing Operations

• Use AI tools natively across the entire marketing lifecycle — from audience research, brief generation, and GTM planning through to creative production, performance analysis, and reporting.
• Use AI-assisted tools to design ad creative, write and test email copy, build landing page variants, and produce campaign reports faster than traditional workflows allow.
• Proactively evaluate and adopt new AI tools that improve campaign velocity, personalisation, or measurement accuracy.

Reporting & Optimisation

• Build and maintain dashboards tracking pipeline contribution, channel performance, funnel metrics, and campaign ROI.
• Report to the Head of Marketing, K12 on a regular cadence — with clear, data-driven recommendations.
• Translate campaign performance into budget reallocation decisions and channel prioritisation recommendations.

Cross-functional Collaboration

• Embed with Product Management throughout the development cycle — from discovery through launch.
• Be the voice of the customer for product and engineering teams.
• Engage global CX and Sales teams across multiple countries to gather insights and drive regional relevance.

About You

• Qualifications
  • Bachelor's or Postgraduate degree in Marketing, Business, Communications, or a related field.
• Experience & Skills
  • 6-8 years of marketing experience in a B2B or B2B2C organisation, with meaningful depth across both demand generation and product marketing.
  • Proven ownership of pipeline from web, digital, lifecycle, events, and other channels — with clear revenue attribution and a track record of improving funnel metrics over time.
  • Demonstrated track record of owning product positioning, messaging, and launches across B2B products.
  • Strong understanding of the B2B funnel: MQLs, SQLs, pipeline stages, SLA management, and what it means to be a genuine partner to a Sales org.
  • Experience with ABM strategy and execution targeting institutional or enterprise buyers.
  • Experience running VoC programmes — structured customer research, interviews, or advisory panels that influenced product or positioning decisions.
  • Hands-on experience with a win/loss analysis programme — not just contributing to one, but shaping how it works.
  • Experience building Sales enablement programmes — training and structured rhythms, not just collateral.
  • Hands-on experience running campaigns across web, paid digital, lifecycle/email, and social. Comfortable owning multiple channels simultaneously.
  • Strong analytical skills — comfortable with attribution modelling, CRM data, dashboard building, and translating funnel insights into clear campaign and budget decisions.
  • Experience owning a B2B website — CMS management, lead capture optimisation, and working with UTMs and tracking logic to ensure all traffic is measurable.
  • Deep proficiency in HubSpot workflows, lifecycle stages, lead scoring, automation, attribution, and reporting.
  • Demonstrated use of AI tools in day-to-day marketing work — for planning, creative, copy, performance analysis, or reporting.
  • Experience launching products in India, South East Asia, China, Australia, or similar markets.
  • Proven ability to lead cross-functional work — aligning with Sales, Content, Product, and external agencies to execute campaigns and drive shared pipeline goals.
• Qualities
  • You are a hands-on operator. You don't just strategise — you build and execute across every channel.
  • You think in customer language — you can take a complex feature and turn it into a message a buyer or school counselor could resonate with.
  • You are a genuine Sales partner — you understand pipeline, speak in revenue terms, and take MQL quality personally.
  • You are the connective tissue between Product, Sales, CX, and UX — aligning people across functions and time zones without needing a title to do it.
  • You are AI-native. You reach for AI tools first and use them to move faster, not as a novelty.
  • You are a natural experimenter — you A/B test instinctively and always run campaigns with a clear hypothesis.
  • You are a strong lifecycle thinker — you understand how to move an audience through a funnel, not just generate top-of-funnel noise.
  • You are data-driven: product adoption metrics, VoC findings, win/loss patterns, and campaign performance all inform how you work.
  • You are equally comfortable at strategic and executional levels — you write the strategy and then go execute it yourself.
  • You are organised and detail-oriented across tracking, attribution, tagging, and reporting.
  • You thrive in fast-paced, high-ownership environments and can manage multiple campaigns simultaneously.
  • You have genuine curiosity about the K12 education space — the counselor workflow, the student journey, and the institutional buying process.

• Workday Master Integration: Leverage our existing Workday-Okta integration to build advanced downstream automation for granular lifecycle events (conversions, international transfers, and rapid offboarding).
• Expert Workflow Design: Architect and maintain mission-critical Okta Workflows to automate Slack channel provisioning, Google Workspace delegation, and Jira project access.
• AI & Bot Innovation: Design and deploy AI-powered bots (Slack/Jira integrations) that allow for natural language access requests and automated troubleshooting of identity issues.

• Unified Endpoint Management: Integrate Microsoft Intune (Windows/Android) and Jamf (macOS/iOS) with Okta to enforce Device Trust and Passwordless authentication.
• Session Security: Implement and manage Okta Universal Logout and session revocation strategies to ensure immediate access termination across all SaaS apps during security incidents.
• Conditional Access: Design policies that ensure only managed, compliant devices can access sensitive corporate data.

• Advanced Logging: Use Okta Expression Language and advanced System Log queries to proactively identify authentication failures or security anomalies.
• Log Analysis: Utilize API-based log streaming to create dashboards that monitor integration health and user adoption metrics.

• The Okta Veteran: 6+ years of dedicated experience with Okta and Okta Workflows. You should be comfortable with advanced workflow logic (API Connectors, Custom Functions, and Error Handling).
• The Device Specialist: Deep hands-on experience with MDM solutions (Intune and Jamf) and how they exchange signals with Identity Providers (IdP).
• The Workflow Automation Power User: Expert at leveraging Workday RaaS (Reports-as-a-Service) and Business Process (BP) events as triggers for complex Okta Workflows. You can parse nested JSON payloads from Workday to drive sophisticated logic for role changes, legal entity transfers, and high-risk terminations with zero manual intervention.
• The Troubleshooter: Expertise in running complex Okta queries and interpreting Syslog data to solve "needle in a haystack" integration issues.
• The Modern Scripter: Proficiency in Python, PowerShell, or JavaScript to fill the gaps where out-of-the-box connectors end.
• The Innovator: A portfolio or history of building automation, bots, or custom tools that improved the employee experience.

#LI-SG2

#LI-Hybrid

Narvar is Growing! We are looking for a high-potential B.Tech graduate with a strong foundation in Artificial Intelligence and process automation to join our team as an AI Consultant for a 12-month engagement. You will work directly on high-impact projects that use AI to automate and transform our HR and Finance functions.

This is a senior internship role with real ownership and accountability. You will be expected to independently drive projects end-to-end — from understanding the problem, designing the solution, building and testing it, and handing it over to business teams. You will work closely with senior HR and Finance leaders, and your output will directly affect how hundreds of employees experience these functions.

Given the compensation and duration, we expect candidates who can demonstrate either strong academic performance in AI/ML, prior projects, or hands-on experience with AI tools. Fresh thinking combined with technical seriousness is what we are looking for.

Day-to-day

HR Projects

Chatbot & Knowledge Management

• Build and maintain an AI-powered HR chatbot that answers employee questions about policies, leave, payroll, and benefits
• Design and test conversation flows for the chatbot — writing instructions, testing responses, and continuously improving accuracy
• Help digitise and organise HR policy documents so the AI can read and reference them correctly
• Analyse common employee queries to identify gaps in HR documentation and recommend content updates

HR Operations Automation

• Automate repetitive HR tasks such as leave tracking, onboarding checklists, exit checklists, and document collection using appropriate tools
• Build AI agents that monitor, update, and distribute HR dashboards to Executives and Managers — reducing manual reporting effort
• Design automated workflows that surface key HR metrics (headcount, attrition, leave utilisation) to the right stakeholders at the right time

Performance Management Automation

• Automate performance review cycle processes — reminder workflows, form collection, status tracking, and escalation nudges
• Build tools to aggregate and visualise performance data for managers, removing manual consolidation from spreadsheets
• Design AI-assisted pipelines to flag review completion rates, identify bottlenecks, and generate summary reports for HR leadership

Talent Acquisition & Recruitment

• Build dashboards and automated reports tracking talent acquisition metrics — pipeline volume, source effectiveness, time-to-offer, and offer acceptance rates
• Design AI-assisted application review workflows to help the recruitment team prioritise and triage high volumes of applications faster
• Automate candidate communication touchpoints such as acknowledgement emails, status updates, and interview scheduling reminders
• Create tools that surface hiring funnel analytics to Hiring Managers and HR leadership in real time

Finance Projects

• Automate routine finance workflows such as invoice processing, expense categorisation, and reimbursement tracking
• Build simple AI-assisted tools to flag anomalies or inconsistencies in financial data
• Create automated reports and dashboards using Google Sheets or similar tools, reducing manual data entry
• Assist in mapping existing manual finance processes and proposing AI-based alternatives
• Test and document automation tools before they are rolled out to the finance team

What we’re looking for

• B.Tech degree in Computer Science, AI/ML, Data Science, Electronics, or related branch — 2024 or 2025 pass-out
• Demonstrable hands-on experience with AI tools — projects, hackathons, internships, or self-built tools all count
• Working knowledge of Python — able to write scripts, use libraries, and debug independently
• Strong understanding of at least one AI/ML concept: LLMs, NLP, classification, automation pipelines, or similar
• Comfortable working with Google Workspace (Docs, Sheets, Drive) and cloud-based tools
• Excellent written communication in English — you will be writing specifications, documentation, and chatbot content
• Ability to manage your own work, meet deadlines, and proactively communicate blockers

Bonus points

• Experience with LLM APIs — OpenAI, Anthropic Claude, or Google Gemini
• Prior internship or freelance project involving AI, automation, or data — even if short
• Familiarity with no-code/low-code tools: Zapier, Make, Botpress, Flowise, or similar
• Basic understanding of HR or Finance workflows from coursework, projects, or prior exposure
• A GitHub profile, portfolio, or any public evidence of what you have built
• Experience with prompt engineering, RAG pipelines, or building chatbots

What you will earn

• By the end of this internship, you will have hands-on experience that most fresh graduates do not get from classroom learning alone:
• How to build and deploy a working AI chatbot using real enterprise tools
• How to design automated workflows that replace manual, repetitive tasks
• How to work with HR and Finance stakeholders to understand their pain points and translate them into technical solutions
• Practical exposure to AI tools, APIs, and no-code platforms used in Indian companies
• How to document, test, and hand over a technical project to a non-technical team
• Real experience you can put on your resume and explain confidently in interviews

Why Narvar?

We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!

From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.

Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

#LI-PR1

#LI-Remote

Opportunity Overview

As the Manager, Machine Learning & Data Science, you will play a key role in building and scaling Cohere Health’s AI capabilities in India. You’ll lead a team of machine learning engineers and data scientists focused on developing and deploying models that automate and augment complex clinical and administrative workflows.

This team is responsible for the full lifecycle of applied machine learning and data science—from problem framing and experimentation to production model deployment and ongoing optimization. You’ll work with structured and unstructured healthcare data to generate insights and power intelligent systems that improve prior authorization and broader clinical decision-making.

As a player-coach, you’ll combine hands-on technical contributions with team leadership, helping to establish best practices, mentor team members, and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders. This is an opportunity to shape both the technical direction and team culture within a growing global organization.

What you’ll do:

• Lead, mentor, and develop a team of machine learning engineers and data scientists, fostering a collaborative, high-performance environment
• Act as a hands-on contributor across the ML/DS lifecycle, including data exploration, feature engineering, model development, evaluation, and deployment
• Design, develop, and deploy machine learning models for retrieval, classification, and generative use cases across structured and unstructured data
• Translate complex business and clinical problems into scalable machine learning and data science solutions
• Establish and uphold best practices for experimentation, model validation, performance tracking, and reproducibility
• Partner cross-functionally with Product, Engineering, Clinical, and Analytics teams to align solutions with business priorities
• Guide the development of scalable data science and machine learning systems, including data preprocessing pipelines and production workflows
• Monitor model performance, identify opportunities for improvement, and drive continuous iteration and optimization
• Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders
• Contribute to hiring and scaling the team in India, including recruiting, onboarding, and coaching team members 

What you’ll need:

Must-haves

• Minimum 8+ years of experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience must be leading technical teams
• Strong hands-on experience building, evaluating, and deploying machine learning models in production
• Solid foundation in statistical methods, experimental design, and model evaluation
• Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn)
• Experience working with large, complex datasets (structured and/or unstructured)
• Strong problem-solving skills with the ability to translate business challenges into analytical solutions
• Excellent communication skills, with the ability to present complex concepts clearly to diverse stakeholders
• Experience working in fast-paced, evolving environments

Nice-to-haves

• Experience in healthcare, particularly with payer, provider, or clinical data
• Experience with NLP, deep learning (e.g., transformers), or generative AI (e.g., RAG)
• Familiarity with MLOps practices and production ML systems
• Experience with Spark or large-scale data processing frameworks
• Exposure to cloud platforms (e.g., AWS, SageMaker)
• Experience working in a global or distributed team environment
• Prior experience in a GCC or building teams in India

Interview Process*:

1. Connect with Talent Acquisition 
2. Meet with the Hiring Manager
3. Behavioral Interview(s)
4. Case Study
5. Interview with Senior Leadership

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

Location Details: Gurugram

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​

This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join our Team

If you are passionate about machine learning and want to make a difference for millions of small businesses, join our DnAI (Data and Artificial Intelligence) team at GoDaddy as a Senior Machine Learning Scientist. You will have the opportunity to build cutting-edge machine learning models and Generative AI solutions to build intelligent software that delight our customers. You will work with highly skilled engineers in building comprehensive solutions to challenging business problems in customer experience, personalization; as well as solve technical problems in model evaluation, simulation and more.

What you'll get to do...

• Develop and implement advanced machine learning algorithms. 
• Build Intelligent Software using Large Language Models (AI Agents). 
• Design and refine ML models to enhance their performance, scalability, and robustness. 
• Assess, design and curate comprehensive evaluations for open-ended GenerativeAI problems. 
• Collaborate with cross-functional teams to integrate ML solutions within broader product and platform initiatives. 
• Drive the exploration and adoption of cutting-edge ML technologies to maintain our competitive edge in the industry. 

Your experience should include...

• 6+ years of overall experience in machine learning related roles.
• Strong knowledge of machine learning algorithms, tools, and techniques, such as supervised and unsupervised learning, deep learning, computer vision, natural language processing, etc. 
• Familiarity with AI assisted coding tools like Cursor, Claude Code or VS Code. 
• Proficient in Python programming language with familiarity with software engineering best practices, such as version control, code review, CI/CD, etc. 
• Proficiency with prompt engineering and large language models (LLM) and Natural Language Processing (NLP).

You might also have...

• Experience building conversational systems. 
• Experience in designing comprehensive evaluations and verification methods. 
• Proficiency in Typescript is a plus.

We've got your back...  We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

THE ROLE

The Data & Analytics team at Ever Pure is looking for a Senior Manager for designing and building an AI-ready data infrastructure powering conversational AI and chatbot experiences for Finance.
This role will lead the end-to-end build, defining the target state, identifying capability gaps, and delivering a phased roadmap with measurable outcomes. A core focus is enabling a conversational, AI-driven Finance experience, allowing stakeholders to access insights through natural language and copilots.

WHAT YOU'LL DO

Finance Control Tower & Data Foundation

• Lead the design and build of the Finance Control Tower
• Establish a scalable, AI-ready data platform for reporting, analytics, and AI
• Deliver unified, trusted views across Finance (revenue, billing, forecasting)

Data Architecture, Semantic Layer & Observability

• Define data architecture and unified models across systems (Salesforce, SAP, NetSuite, Zuora)
• Build a semantic / metrics layer to standardize business definitions
• Implement data management and observability (quality, lineage, reliability)

Conversational AI & AI Enablement

• Enable natural language access to Finance data via chatbots and copilots
• Build RAG-based architectures using structured and unstructured data
• Develop embeddings and semantic context layers for business-aware insights
• Leverage platforms like Snowflake Cortex (or similar) for search, summarization, and classification

Data Engineering & AI Integration

• Build and scale data pipelines and AI-ready datasets in Snowflake (or similar)
• Integrate enterprise data sources (SFDC, NetSuite, Zuora)
• Enable LLM-driven use cases (forecasting, anomaly detection, variance analysis)
• Ensure outputs are accurate, explainable, and traceable

We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• 15+ years in data engineering, analytics, or related roles
• Experience building modern data platforms / data products at scale
• Strong expertise in:
• SQL, data modeling, ETL/ELT
• Semantic / metrics layer design
• Data governance, quality, and observability
• Experience with Snowflake (or similar) and Python
• Exposure to:
• Conversational AI / chatbot systems
• RAG, embeddings, vector search
• LLM frameworks and prompt design
• Understanding of Finance data (ARR, MRR, revenue) preferred
• Strong execution, stakeholder management, and communication skills

#LI-ONSITE

THE ROLE

We are seeking a highly skilled and hands-on Senior Finance Data & Analytics Engineer (IC role) to lead the design and development of the Finance Data Cube, enabling enterprise-wide insights into Customer Lifetime Value (CLTV), Contribution Margin, and other key financial metrics.

WHAT YOU'LL DO

• Design, build, and own the Finance Data Cube, integrating financial, customer, and operational datasets.
• Model data to support CLTV, Contribution Margin, and other profitability KPIs across multiple dimensions (customer, product, LOB, geography, etc.)
• Be a data architect for Finance , bring different data into cohesive and answer critical questions
• Leverage AI tools to automate data summarization, anomaly detection, and narrative insights for Finance stakeholders.
• Scale data infrastructure to support large volumes and complex financial models.
• Build and manage Semantic Layer models to standardize business metrics and enable self-serve analytics
• Translate complex financial concepts and KPIs into scalable, maintainable data models.
• Implement strong controls for data quality, lineage, and governance.
• Maintain clear documentation of data transformations, metric definitions, and AI model logic.
• We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• Experience: 8+ years in Finance Data Engineering, FP&A Analytics, or Financial Systems, with exposure to AI/ML-based analytics(added advantage)
• Proficiency with Snowflake and modern data stacks with strong SQl and data modeling expertise 
• Deep understanding of finance data set , SAP , Contribution margin, CLTV would be an added advantage
• Experience with data orchestration tools (Airflow, dbt) and tableau platform
• Hands-on experience with Python, PySpark, or R for automation and model integration.
• Proven ability to translate financial logic into scalable data models.
• Experience in Cortex Analyst/Search components to enable AI/ML-driven insights, natural language querying, and intelligent data discovery is preferred. 
• Knowledge of predictive modeling, time-series forecasting, and generative AI in analytics.
• Ability to evaluate and apply AI responsibly in financial contexts.

 #LI-ONSITE

The Technical Success Manager Lead will oversee and guide a team of Technical Success Managers while directly contributing to strategic customer engagements. This role will be pivotal in aligning customer needs with ABBYY’s solutions to maximize value realization. As a leader, you will ensure best practices in technical success and foster a culture of customer-centric innovation. 

Roles & Responsibilities 

Leadership & Team Management: 

• Lead, mentor, and support a team of Technical Success Managers, ensuring alignment with company goals and customer success objectives.
• Establish frameworks and processes for value discovery and delivery, ensuring consistency across customer engagements.
• Serve as an escalation point for complex customer challenges, collaborating with internal teams to resolve issues promptly.

Strategic Customer Engagement: 

• Conduct high-level value discovery sessions with strategic accounts, ensuring customer goals and business objectives are clearly defined and met.
• Build and maintain strong relationships with executive-level stakeholders in customer and partner organizations.
• Collaborate with account managers, pre-sales teams, and other technical leaders to deliver seamless customer experiences and drive adoption.

Process Improvement & Innovation: 

• Identify opportunities to streamline customer success processes and introduce scalable, repeatable frameworks for customer engagement.
• Advocate for customer needs within ABBYY, driving initiatives to enhance product capabilities and customer satisfaction.
• Develop and refine success metrics to measure team performance and customer outcomes.

Enablement & Advocacy: 

• Design and implement training programs for customers and partners to promote product adoption and success.
• Lead initiatives to gather, analyze, and act on customer feedback to improve products and services.
• Drive customer advocacy efforts, including case studies, references, and success stories.

Operational Excellence: 

• Monitor and manage team workloads, ensuring efficient delivery of customer success projects.
• Analyze customer usage patterns, adoption trends, and churn risks to guide proactive engagement strategies.
• Report regularly to senior leadership on team performance, customer health, and strategic insights.

Requirements 

Experience & Skills: 

• 7+ years in a customer-facing technical role (e.g., Pre-Sales, Professional Services, Technical Account Management), with at least 3 years in a leadership capacity.
• Proven experience in SaaS environments, with a deep understanding of subscription-based business models.
• Expertise in technologies such as OCR/ICR, Intelligent Document Processing, Enterprise Automation, RPA, ECM, BPM, or Process Mining.

Leadership Qualities: 

• Strong track record of building and leading high-performing teams in customer success or related disciplines.
• Exceptional communication and interpersonal skills, with the ability to engage diverse stakeholders, from technical teams to executives.
• Demonstrated ability to drive alignment across departments and manage competing priorities effectively.

Technical Acumen: 

• Strong ability to bridge the gap between technology and business, translating customer needs into actionable solutions.
• Experience with software implementation, technical troubleshooting, and delivering enterprise-scale solutions.
• Proficiency with analytics platforms and advanced skills in MS Office Suite or similar tools.

Soft Skills: 

• A proactive problem solver with a customer-first mindset and a strong sense of ownership.
• Excellent project management and prioritization skills, capable of overseeing multiple high-impact initiatives simultaneously.
• Comfortable working in a fast-paced, dynamic environment with changing priorities.

Here's a snapshot of our local benefits:

• 18 Days of Paid Time Off Annually
• Medical, Accidental, and Life Insurance
• Weekly Wellness Sessions
• Monthly Healthcare Allowance

#LI-MM1

Okta seeks a skilled Staff Full Stack Engineer with expertise in NetSuite and/or  Oracle Fusion Cloud Applications. As part of our Business Technology team, you will be responsible for developing and optimizing full-stack solutions, including custom scripts, workflows, integrations, and system enhancements for both NetSuite and Oracle Fusion to improve business processes and scalability. This role will report to the Manager in Bangalore, India. We’d love to hear from you!

Job Duties and Responsibilities

• Design, develop, and maintain full-stack solutions for Finance Tech stack like NetSuite, Coupa and Oracle Fusion Cloud Applications etc., using any of the full-stack applications like Node Js/React
• Develop and maintain robust off-platform integration scripts using Python & LangChain to manage data transfer and interactions between NetSuite (via SuiteTalk or RESTlets) and AI Platforms
• Architect and implement scalable, secure, and cost-efficient cloud-native solutions on AWS for RAG, MCP, and Agentic AI (LangGraph) 
• Closely work with the BT Product Manager to design, develop, test, implement & support system solutions primarily in Finance Technology
• Provide technical consultation, best practices, and problem resolution for AI and Agentic AI for the Finance tech stack NetSuite, Oracle Fusion, and associated integrated systems
• Support & resolve production issues across the full application stack
• Develop and maintain integrations with third-party applications via REST/SOAP APIs
• Design and implement custom Generative AI solutions using the SuiteScript Generative AI API for practical NetSuite use cases and explore similar capabilities in Oracle Fusion

Required Skills:

• 9+ years in Python and its libraries (e.g., Pandas, Boto3) for data manipulation, ETL processes, and developing serverless functions to interact with foundational AI services on platforms like AWS Bedrock.
• Deep hands-on experience with AWS solutioning, including designing and deploying production applications using core services such as AWS EC2, AWS Lambda, Amazon S3, Amazon RDS, and API Gateway. Familiarity with Infrastructure as Code (IaC) tools like CloudFormation or Terraform is essential.
• Proficiency in NetSuite development experience (SuiteScript, SuiteFlow, SuiteTalk).
• Experience with SuiteCloud tools, REST/SOAP APIs, and third-party integrations.
• Experience with the SuiteScript Generative AI APIs to integrate LLM capabilities for advanced scripting solutions
• Strong understanding of Finance Business processes (Order Management, Billing, Vendor bill, etc.).
• Proficiency in JavaScript, SQL, and related web technologies
• Configure NetSuite modules to align with business needs, including leveraging Prompt Studio to customize and manage NetSuite AI functions like Text Enhance.
• Ability to drive and architect solutions with other developers, focusing on maximizing the value of embedded NetSuite AI capabilities
• Working Experience on the MCP and familiar with SaaS MCP connectors, like NetSuite MCP or similar
• Working experience with foundational AI services, with a desire to use a unified platform like AWS Bedrock for Generative AI development and deployment
• Nice to have some core Amazon Machine Learning (ML) services, specifically AWS SageMaker (for building, training, and deploying custom ML models), AWS Comprehend (for natural language processing and text analytics), and  Retrieval Augmented Generation (RAG)

Education and Certifications

• A Bachelor’s degree in Computer Science, Information Systems, or equivalent years of industry experience
• AWS cloud Certification or any ERP foundation certificate is a plus

#P25153_3431422
#Linkedin_Hybrid

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

BOLD is seeking a senior professional to implement and run Testing and Quality Assurance specifically designed for AI-driven products and Data Science workflows. In this role, you will bridge the gap between traditional software testing and modern machine learning evaluation. You have a great team management and organizational skills. You’ll have a broad mastery of capabilities, techniques, technologies and tools in the Testing and QA domains. You’ll be handling QA teams of various sizes and expertise.

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them up to to date with technology.

WHAT YOU’LL DO 

• Develop and own the QA strategy for AI-driven features, focusing on model accuracy, data drift, and performance metrics (Precision, Recall, F1-score).
• Implement state-of-the-art AI tools (e.g., GitHub Copilot, or custom LLM agents) to automate test case generation, code analysis, and synthetic data creation.
• Oversee the testing of Generative AI outputs, implementing "LLM-as-a-judge" frameworks to evaluate hallucination rates, toxicity, and prompt adherence.
• Develop and own BOLD’s quality framework from product development through to production
• Should be able to drive the initiatives (both Business and QA) in his area along with needed smooth coordination across the board to ensure a timely achievement of goal.
• Take part in Requirement Analysis, Sprint planning, Bug triage meetings.
• Liaise with product, development, and infrastructure teams to collaborate on delivery of high quality, high performance, and high availability applications
• Develop quality scripts with needed coverage to ensure defect free releases.
• Manage and mentor team members to maximize output and efficiency and promote a team culture of quality and fun
• Motivate, Encourage, Guide Teams maintaining equilibrium and satisfaction level.
• Give technical/logical solutions to problems faced by the teams and remove hurdles blocking releases.
• Evaluate and suggest new tools and technologies

WHAT YOU’LL NEED

• Solid understanding of the Machine Learning lifecycle (EDA, Training, Evaluation, Deployment).
• Experience using LLMs (GPT, Claude, Llama) and AI-coding assistants to accelerate the testing lifecycle.
• Experience in a high volume, high throughput web/ecommerce environment.
• Hands-on experience with UI/API automation (Selenium, Playwright, or Cypress) integrated with AI-driven healing capabilities.
• Experience with web service technology like XML, REST, SOAP
• Knowledge on any of the query language like SQL, JQL etc.
• Experience in testing complex web and mobile apps.
• Strong application architecture and technical knowledge
• Strong knowledge of web concepts, including web performance infrastructure.
• Able to play the role of a scrum master, with strong coordination skills
• Knowhow of basic UX standards, SEO/ SEM concepts and key tracking matrices
• Strong communication skills 

EXPERIENCE- 

• Module Lead, QA (AI/ML & Automation)- 5 years+

BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 

WHAT YOU’LL NEED 

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Should have done one or more projects involving fine-tuning with LLMs 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.    

EXPERIENCE- 

• Software Engineer- 2.5 years+
• Senior Software Engineer-4.5 years+

#LI-SV1

About the Role

NICE is seeking a talented AI Engineer to accelerate innovation across the APAC region by leading AI-centric Proof of Concepts (POCs) and Pilots alongside our extended solution and sales engineering teams. This role sits at the intersection of cutting-edge AI development and customer-facing technical delivery, with a special focus on Agentic AI solutions that push the boundaries of what is possible with intelligent automation and large language models.

The AI Engineer will work hands-on to design, build, and demonstrate AI-powered solutions, translating complex technical capabilities into tangible business value for customers across APAC.

How will you make an impact?

Agentic AI POCs & Pilots

• Design and build Agentic AI proofs of concept

     Architect and develop end-to-end Agentic AI solutions demonstrating autonomous decision-making, multi-step reasoning, and task orchestration across APAC customer engagements.

• Prototype rapidly

     Build lightweight, demonstrable prototypes using LLMs, agent frameworks, and NICE /Cognigy platform APIs to showcase the art of the possible.

Development & Engineering

• Develop and integrate APIs, webhooks, and microservices connecting LLMs and AI models to enterprise platforms and CX workflows.
• Build and maintain reusable AI accelerator assets, code templates, and demo environments for the extended APAC team.
• Implement prompt engineering strategies, RAG pipelines, and agent orchestration frameworks LLM & AI Model Expertise
• Apply knowledge of large language models (GPT-4, Claude, Gemini, Llama, etc.) to design appropriate solutions for customer use cases.
• Evaluate and select the right model, fine-tuning approach, or retrieval strategy for each POC based on accuracy, latency, and cost requirements.
• Stay current with the rapidly evolving LLM ecosystem including model releases, agent frameworks, and emerging AI tooling.

Collaboration & Knowledge Sharing

• Contribute to internal playbooks, documentation, and demo libraries to uplift the broader team’s AI capabilities.
• Engage with customers directly to understand requirements and translate them into practical AI solution designs.

Have you got what it takes?

• Bachelor’s degree in computer science, Software Engineering, or a related field or equivalent experience.
• 4-8 years of software development experience in developing high performance, highly available and scalable enterprise-grade software products that can perform, scale, and integrate into a broad enterprise ecosystem.

Programming proficiency:

.

• Experience with REST APIs, JSON, cloud SDKs
• Familiarity with data processing, vector databases and embedding pipelines for RAG architecture.
• Ability to debug, iterate quickly, and deliver working demos under tight timelines.

AI & Machine Learning Understanding

• Solid conceptual and practical understanding of machine learning fundamentals, NLP/NLU, and generative AI.
• Experience designing or building Agentic AI systems — including tool use, memory, planning, and multi-agent coordination.
• Understanding of responsible AI practices, hallucination mitigation, and evaluation methodologies for LLM outputs.

LLM Usage & Prompt Engineering

• Proficient with LLM APIs     including OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, and open-source models via Hugging Face or Ollama.
• Strong prompt engineering skills: few-shot prompting, chain-of-thought, structured outputs, and system prompt design.

Version Control & Collaboration Tools

• GitHub / Git proficiency:

     Comfortable with branching strategies, pull requests, code reviews, and collaborative development workflows.

• Ability to manage, share, and version AI demo assets and code in shared repositories accessible to the extended team.
• Experience with CI/CD basics and familiarity with tools such as GitHub Actions, or similar pipelines, is advantageous.

.

You will have an advantage if you also have:

• Experience with NICE CXone, Cognigy (conversational AI & agent orchestration platform), or similar CCaaS / conversational AI platforms.
• Knowledge of the APAC technology landscape and experience working with enterprise customers in the region.
• Background in contact centre, CX, or enterprise SaaS environments.
• Exposure to voice AI, speech-to-text/text-to-speech pipelines, or real-time AI in contact Centre contexts.

What’s in it for You?

Join an ever-growing, market-disrupting, global company where teams — comprised of the best of the best — work in a fast-paced, collaborative, and creative environment. As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate about AI, innovative at heart, and excited to constantly raise the bar on what intelligent technology can do, you may just be our next NICEr!

Enjoy NICE-FLEX!

At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10692                

Reporting into: Director,Solution Engineering

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

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 

About The Position:
To serve as the strategic leader of our engineering operating system. You will own the health, configuration, and insights derived from the Jira and Jellyfish tools, ensuring our leadership has a crystal-clear view of engineering investment, velocity, and health across the entire organisation.

We expect this candidate to be an "AI-First" practitioner, using agentic tooling to automate the mundane and focus on high-leverage organizational improvements.

What You Will Do:

Tooling Architecture & Governance

• Jira Cloud Expert: Design, build and maintain complex workflows, permission schemes, and automation rules at scale.
• Jellyfish Orchestration: Map Jira "Signals" to Jellyfish allocation buckets. Ensure the data reflects the true "Investment Distribution" (e.g., separating KTLO/Maintenance from Innovation).
• System Integrity: Standardize issue types and field usage across 20+ squads to ensure Jellyfish insights are statistically valid.

AI-Augmented Operations

• Natural Language Querying: Use Atlassian Intelligence to translate plain-English requests into complex JQL for instant reporting.
• AI Impact Analysis: Leverage Jellyfish AI Impact to measure how AI coding assistants (Copilot, Cursor) are actually shifting our "Time to Deliver" and code quality.
• Workflow Automation: Integrate  AI Agents to handle "ticket hygiene"—automatically flagging stale issues, summarizing long comment threads for stakeholders, and triaging incoming requests.
• Synthetic Insights: Use LLMs (Claude/ChatGPT) to synthesize monthly Jellyfish data into executive-level narratives that explain the "Why" behind the "What."

Strategic Delivery Insights

• DORA & Flow Metrics: Monitor Cycle Time, Lead Time, and Deployment Frequency to identify systemic bottlenecks. Also identify improvement opportunities.
• Capitalization Reporting: Partner with Finance to use Jellyfish data for R&D tax credit reporting and labor capitalization.
• Stakeholder Engagement: Work with stakeholders on triaging and aligning requirements in conjunction with tool administrators for a seamless rollout

What We Are Looking For:  

Minimum Requirements:

• Experience: 
• 5+ years in Engineering Operations (EngOps), Program Management, or a similar data-heavy engineering role.
• Tooling Expertise: 
• Jira Cloud: Expert-level administration skills.
• Jellyfish: Power user proficiency.
• Analytics & Metrics: 
• Deep understanding of Agile metrics and Engineering Investment categories.
• Strong knowledge of DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service).
• Technical Skills: 
• Advanced proficiency in Jira Automation and JQL.
• Foundational knowledge of the SDLC process, Scrum, and SAFe methodologies.
• AI Proficiency: 
• Comfortable leveraging AI agents and LLMs for data analysis and scripting tasks.

 Preferred Skills & Qualifications

• Programming & Integration: Ability to write basic Python or JavaScript for API integrations.
• Cloud & Version Control: Experience with GitHub and AWS is considered a significant bonus.

G-P helps organizations build global teams in minutes, not months. As part of this mission, we’ve created an indispensable AI agent for HR leaders, G-P Gia™ .

Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over a decade of global employment and legal expertise and 100,000+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.

About The Position:

We’re building GIA — AI for General Counsel, in-house legal teams, and HR teams. GIA is a startup that demands extreme ownership, relentless execution, and zero tolerance for waiting on someone else to make the call. This role sits at the intersection of data science, data engineering, and product analytics. You build the pipelines, run the analysis, train the models, and — most importantly — tell us what the data means for the product. Not dashboards for the sake of dashboards. Insights that change what we build next.

What You Will Do:

• Build and own data infrastructure — pipelines, warehousing, ETL/ELT, data quality; make sure the foundation is solid
• Analyze product usage and user behavior — identify patterns, segment users, surface what matters from the noise; think like a product person, not just a data person
• Build models that ship — LLM-based systems, traditional ML (classification, clustering, NLP), evaluation frameworks; whatever the problem needs
• Define and track the metrics that matter — activation, retention, engagement, PQLs; connect data to product and GTM decisions
• Run experiments and measure impact — A/B tests, causal analysis, cohort studies; rigorous but fast
• Turn data into product conviction — you don’t just hand off charts, you tell the team what to do and why

What We Are Looking For:  

Minimum Requirements: 

• 5+ years across data science, data engineering, and analytics — you do all three, not just one
• Strong SQL and Python — complex queries, data modeling, scripting, analysis; this is your daily toolkit
• Databricks or equivalent modern data platform experience (Snowflake, BigQuery)
• LLM experience — fine-tuning, prompt engineering, embeddings, RAG, evaluation; not just API calls
• Traditional ML depth — classification, regression, clustering, NLP, feature engineering; you pick the right tool for the problem
• Product mindset — you filter signal from noise, understand user behavior, and connect analysis to product decisions
• Pipeline engineering — you build reliable, scalable data pipelines, not notebooks that break in production
• Clear communicator — you present findings to non-technical stakeholders with clarity and conviction

Preferred Qualifications: 

• Experience at an early-stage startup or as a founding data hire
• Built product analytics from scratch — instrumentation, event taxonomy, dashboards, self-serve reporting
• Legal or HR domain experience
• Experience with LLM evaluation and observability (tracing, scoring, drift detection)
• Familiar with dbt, Airflow/Dagster, Spark, or similar orchestration and transformation tools

How we evaluate

• Give you a real dataset and ask what you’d do with it — we want product thinking, not just technical chops
• Walk us through a time your analysis changed a product decision
• Design a data pipeline or model architecture on the whiteboard
• Show us how you’d instrument and measure a new feature from scratch

Interested? Reach out with an example of an insight you uncovered that changed what a team built.

What's the Role All About? 

The Software Engineer is a customer-facing, billable role responsible for implementing, configuring, and delivering AI-driven and Conversational AI solutions across the NICE CXone ecosystem.  As a hands-on technical contributor, you will build integrations, configure conversational AI platforms, and ensure high-quality execution of project deliverables.  

How Will You Make an Impact? 

• Partner with business stakeholders to map current workflows, identify ROI-backed opportunities (reduced effort, improved employee experience, measurable efficiency gains), and define future-state toAI-enabled processes.
• Design, build, and iterate AI solutions and automations in n8n, Copilot Studio, and other AI/automation tools; create reliable agents and assistants that remove manual work.
• Understand and work within NiCE internal processes and systems (e.g., CRMs, knowledge bases, ticketing/support tools, and operational platforms) to ensure solutions fit real-world constraints.
• Collaborate with IT and Developers when needed to overcome technical obstacles, integrate securely with enterprise systems, and scale solutions.
• Enable and upskill internal support teams to use AI effectively—through reusable patterns, playbooks, coaching, and hands-on problem solving.
• Maintain expertise in modern AI approaches and apply them pragmatically to internal operations, including LLMs, RAG, GPT-based assistants, Copilot ecosystems, MCP servers, APIs, JSON, and light scripting. Use AI tools to debug and resolve workflow or code errors.

Have You Got What It Takes? 

• 2+ years of experience in solutioning, business process improvement, operations consulting, or similar roles driving cross-functional change.
• Proven ability to translate operational needs into practical AI use cases and deliver outcomes against clear success metrics.
• Strong, applied knowledge of AI and NLP technologies (LLMs, RAG, GPTs, Copilot-style assistants, AI agent patterns, MCP servers).
• Hands-on experience building automations/assistants with n8n (or comparable orchestration tools); comfort developing in Copilot Studio or similar platforms.
• Working knowledge of API integrations, JSON, and basic coding/scripting; able to use AI tools to debug and manipulate code or automation errors.
• Demonstrated curiosity and ongoing personal or professional use of AI tools to improve workflows—someone who experiments, learns fast, and brings practical AI habits into the role.
• Excellent stakeholder management and communication skills, with the ability to drive adoption and help others become effective with AI.
• Comfortable operating in a fast-paced environment, balancing multiple initiatives and iterating quickly based on feedback and results.

What’s in it for you? 

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! 

Enjoy NiCE-FLEX!  

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. 

About NICE

NICE Ltd. (NASDAQ: NICE) is an innovation leader in AI, cloud, and digital solutions, serving over 25,000 global businesses, including 85 of the Fortune 100 corporations. With over 8,500 employees across 30+ countries, NICE software handles more than 120 million customer interactions and monitors over 3 billion financial transactions daily. NICE is committed to diversity and inclusion, ensuring equal opportunities for all candidates.

Requisition ID: 10542
Reporting into: Tech Manager
Role Type: Individual Contributor

Overview

We are seeking a Director of Engineering – Digital to lead the digital transformation of our contact center technology ecosystem. This role will drive the development and implementation of cutting-edge AI-powered customer engagement platforms, cloud-based contact center solutions, and omnichannel communication strategies.

The ideal candidate will bring deep expertise in cloud contact centers (CCaaS), conversational AI, automation, and customer experience (CX) optimization, along with strong technical depth and leadership capabilities.

What You’ll Do

As a Director of Engineering at Five9, you will:

• Define and execute the technology roadmap for the digital campaign management platform, ensuring alignment with business goals
• Lead and mentor a team of engineers, fostering a culture of innovation, collaboration, and technical excellence
• Architect and oversee the development of AI-driven features that enhance connect rates and conversion rates across multiple digital channels
• Ensure scalability, security, and reliability in a multi-tenant SaaS environment
• Collaborate with product managers, designers, and data scientists to develop and deploy cutting-edge campaign optimization techniques
• Stay ahead of emerging technologies and industry trends, integrating best practices into the development process
• Establish engineering best practices, CI/CD pipelines, and DevOps methodologies to improve development velocity
• Manage engineering budgets, resource allocation, and vendor relationships
• Work closely with operations, customer service, IT, and business leaders to align digital solutions with company objectives
• Ensure 99.99% uptime, scalability, and resilience of digital platforms to handle high call volumes

What You Bring

As a Director of Engineering at Five9, you will need:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 12+ years of software engineering experience, with at least 5 years in a leadership role
• Proven track record of building and scaling AI-powered SaaS products, preferably in digital marketing or customer engagement domains
• Expertise in modern software architectures, cloud computing (AWS/Azure/GCP), and microservices-based development
• Strong experience with AI/ML technologies, NLP, and predictive analytics for customer engagement
• Hands-on experience with programming languages such as Java, and modern front-end frameworks such as React, with strong full-stack engineering capabilities
• Strong technical depth with the ability to be hands-on when needed, and comfort leveraging agentic coding tools and AI-assisted development environments to improve engineering productivity
• Knowledge of campaign management, customer journey automation, and omnichannel engagement strategies
• Experience working with social media and messaging APIs (e.g., WhatsApp Business API, Instagram API, etc.)
• Strong understanding of data privacy, security compliance, and scalability challenges in multi-tenant SaaS platforms
• Excellent leadership, communication, and problem-solving skills
• Experience working in a fast-paced, high-growth or startup environment
• Familiarity with A/B testing, personalization, and analytics-driven product development
• Understanding of GDPR, CCPA, and other data protection regulations

Why Join Us

• Lead the digital evolution of a high-impact contact center technology ecosystem
• Work on AI-driven automation and CX optimization with cutting-edge technologies
• Opportunity to shape the future of AI-powered customer engagement technology
• Collaborate with a talented and passionate team dedicated to innovation
• Be part of a dynamic and customer-focused organization driving innovation in customer engagement
• Competitive salary, benefits, and career growth opportunities

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

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.

MAKE AN IMPACT

Experience Level: 8-20 Years 

Locations – Pune / Bengaluru / Hyderabad / Gurugram / Chennai/ Mumbai

Notice period – Immediate - 30 days only

Mandate Skills – 

• Role/Function: Business Analyst, BA, Conversation Banking BA, Chat BA, Conversational AI BA
• Domain/Capability: Chat on Digital Journeys, Conversational Banking, AI Chat, Chatbot, Voicebot, Digital Banking Journeys
• Tech/Platforms:
• Skills: Agile, Jira, Confluence, NLU, Customer Experience, Digital Transformation

Please see JD below:

• Job Description

  • Job Description – BA (Conversation Banking – Chat):

    Must Have Skillsets:

    • Strong experience working on Chat-based digital journeys across mobile and web platforms.
    • Hands-on exposure to Chatbot and Voicebot implementation leveraging AI/Gen AI technologies.
    • Knowledge and practical experience with NLU (Natural Language Understanding) platforms, such as:
    • RASA
    • Google Dialogflow
    • Poly AI
    • Sierra
    • Dyna (or similar platforms)

    Good to Have Skillsets:

    • Relationship Manager (RM) chat channel experience (e.g., WhatsApp, WeChat, or other messaging channels).
    • Exposure to Genesys Cloud contact center integration.

    Additional Skills:

    • Strong business analysis skills, including requirements gathering, user story creation, backlog refinement, and Agile ways of working.
    • Ability to collaborate across Product Owners, Digital Product Managers, UX teams, and technical delivery teams.
    • Excellent stakeholder management, communication, and problem-solving skills.

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. Youʼll 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 deep learning and Gen AI 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 deep learning and Gen AI, we would like to talk to you.

Role: Gen AI Presales Leader

Key Responsibilities:

• Build and deliver customized GenAI demos (PoCs, proposals) that use client-relevant data or scenarios leveraging multi-modal GenAI (text, image, tabular data)
• Collaborate with sales and practice teams to understand client needs and design relevant , scalable proof-of-concepts.
• Conduct deep-dive discovery sessions to identify and translate business objectives into AI solution opportunities, avoiding “tech-first”
• Build reusable demo assets and frameworks to accelerate future demo
• Incorporate real-world datasets and scenarios for maximum client
• Track demo impact on deal progression and refine offerings
• Track competitor solutions and create battlecards to position offerings
• Bring feedback from prospects into product roadmaps for stronger market
• Provide input on proposal writing, RFP/RFI responses with industry specific Gen AI case
• Stay updated on GenAI trends (e.g., retail media networks, synthetic consumer research).

Desired Experience & Education:

• 12+ years of experience in Data Science, with proven pre-sales
• Strong technical expertise in ML, NLP, GenAI, and data
• Experience designing end- to- end data science/ AI solutions for business problems
• Excellent storytelling skills to translate technical capabilities into business
• Familiarity with multiple domains (e.g., CPG, pharma, BFSI)
• Excellent written and verbal communication skills
• Familiarity working with international stakeholders in a consultative environment
• Knowledge of working with cloud platform (Azure / AWS)
• Knowledge of Software Engineering practices

About the Opportunity

The Impact you bring to Cognite

Key Responsibilities

• Take product requirements and independently design, train, test, and deploy ML models (e.g., NLP, Vision-Language Models) for document parsing, layout analysis, and entity matching.
• Write high-quality, scalable production code (Python). Wrap your ML models into robust RESTful or gRPC APIs and integrate them seamlessly into existing industrial master data systems and workflows.
• Implement and maintain CI/CD pipelines for your models. Navigate complex deployment environments, manage containerized applications (Docker/Kubernetes), and optimize inference bottlenecks.
• Work with Principal engineers to translate high-level system architectures into concrete, scalable data pipelines and production-ready microservices.
• Design automated testing for ML pipelines. Monitor deployed models in production for data drift, latency, and accuracy, proactively implementing retraining strategies.
• Collaborate effectively with product managers to define ML capabilities. Provide code reviews and informal technical mentorship to engineers.

Required Skills and Qualifications

• Bachelor’s or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
• 6–10 years of industry experience in software engineering with a strong focus on machine learning, MLOps, and API development.
• Strong programming skills in Python with experience using backend web frameworks (e.g., FastAPI, Flask, Django) to serve models.
• Solid expertise in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
• Hands-on experience with containerization (Docker, Kubernetes), Linux environments, CI/CD tools (GitHub Actions, Jenkins), and deploying models on cloud platforms (AWS, Azure, or GCP).
• Solid understanding of software architecture, data structures, and algorithms to ensure performant code.
• Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Ray, Dask) and orchestrating complex data workflows (e.g., Apache Airflow, Dagster, Prefect).

What Sets your Role Apart

• Independently define the technical ML/SWE approach for ambiguous feature requests and deliver to production.
• Recognize the model is a small part of the solution; expertly manage aspects like API rate limiting, asynchronous processing, and robust data routing around ML components.
• Possess hands-on experience maintaining production ML models and designing resilient systems against poor data quality..

Preferred Qualifications

• Proven experience fine-tuning and deploying multimodal models for visual data and engineering diagrams in live environments.
• Built robust, production-grade RAG pipelines, expertly utilizing Vector/Graph Databases for high-accuracy entity retrieval.
• Familiar with orchestrating multi-step reasoning using frameworks like LangGraph or AutoGen for real-world problem-solving.
• Strong understanding of advanced OCR, layout parsing, and techniques for consistent structured JSON extraction from complex industrial PDFs. Manufacturing/OT dataset experience preferred.
• Ability to optimize LLMs/VLMs for inference latency (quantization, TensorRT, vLLM), potentially in constrained, on-premises environments.
• Experience with modern data lake/lakehouse architectures (Delta Lake, Iceberg, Databricks) for efficient querying and preprocessing of petabyte-scale unstructured data for LLM/VLM training and RAG.

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Job Title: Manager, Software Engineer

Locations: Bangalore

Reports to: VP, AI Engineering

 A quick snapshot…

Conga is looking to hire a Manager, Software Engineering to join our extremely talented AI Engineering team. As an Engineering Manager at Conga, you’ll lead a team of software engineers working on our next generation AI Solutions. This team will be responsible for building statistical and machine learning models that support product features across the company. You’ll get to work directly with other Engineering Managers, Architects, Data Scientists, Product Managers, and Directors, all of whom make up the larger team. In this highly collaborative environment, you will have the opportunity to grow as a leader and help mentor others.

This position requires experience leading software engineering initiatives, knowledge of AI/ML solutions, as well as excellent people and time management skills. This role will be reporting to the VP of AI Engineering and will be a key engineering leader inside the Conga AI Pillar. The role requires you to collaborate with other leaders at Conga and guide your team to deliver high quality software solutions in a timely manner. The ideal candidate for this position is passionate about people, process, technology, and delivering customer values.

Conga works in an agile environment where there are daily stand-ups, code reviews, and constant communication within each self-managed cross-functional team. The ability to communicate effectively with other Engineering and Product leaders, as well as work closely with other your team members are key components for success in this position.

Why it’s a big deal…  

8+ or more years of experience in the Software Engineering industry with a record of increasing responsibility leading software development initiatives, and 3+ years managing teams.

Deep understanding of the Software Development Lifecycle (SDLC) and Machine Learning Lifecycle (MLL).

Lead and drive the strategy, vision and roadmap for building robust, scalable AI/ML foundations and platforms — including but not limited to:

•  Feature stores
• Distributed ML model training
• Model versioning and evaluation
• Monitoring, drift detection, and automated retraining pipelines
• Responsible AI, model explainability, and fairness assessments

Experience with productionizing ML models and integrating them into real-time and batch applications. Work closely with data science partners and domain engineering teams to understand AI/ML use cases and build corresponding foundations for personalization, NLP, forecasting, recommendations, and generative AI.

Experience using a popular programming language such as: Python (preferred), Java, C#, Scala, etc.

Solid understanding of modern software development practices including object-oriented programming, concurrency, design patterns, microservices architecture, RESTful API design, and test-driven development.

Experience with software testing concepts and tools: white/black box testing, coverage analysis, mocking, PyTest/xUnit, Selenium, etc.

Hands-on experience with GCP technologies such as BigQuery, GKE, GCS, DataFlow, Kubeflow, and Vertex AI — or equivalent services in AWS and/or Azure.

Familiarity with ML frameworks and tools such as TensorFlow, PyTorch, MLflow, scikit-learn, HuggingFace Transformers, etc.

Strong experience with Infrastructure-as-Code and CI/CD tools used to automate deployment to cloud platforms: Terraform, GitHub Actions, Concourse, Ansible, etc.

Excellent leadership, decision-making, and communication skills, with the ability to translate business needs into engineering outcomes.

Experience with AI product lifecycle management, including experimentation tracking, model governance, and release management.

Experience with Python is ideal; Java/Spring is a strong plus.

Education: Bachelor’s degree in computer science, Engineering, or a related technical field; Master’s degree preferred 

Are you the person we’re looking for?  

Provide engineering leadership and mentorship to a team of software engineers.

Be a strong engineering leader responsible for executing the Conga AI roadmap using agile practice.

Experience implementing scalable data and AI/ML solutions in a product-driven technology environment.

Manage, lead, and motivate cross-functional, interdisciplinary teams of software engineers to achieve strategic and tactical business outcomes.

Mentor and grow engineers in your team, fostering a culture of teamwork, accountability, and continuous improvement.

Demonstrated ability to skillfully hire, coach, and performance manage a team of technology professionals.

Partner with others at Conga to ensure engineering tasks are understood, broken down, and implemented to the highest of quality standards.

Collaborate with members of the team to solve challenging engineering tasks on time and with high quality.

Encourage skill growth of your team members.

Assist and adhere to enforcement of project deadlines and schedules.

Actively communicate with team members to clarify requirements and overcome obstacles to meet the team goals.

Highly technical, confident at the operational management level and comfortable in an engineering-heavy organization.

Track record of being a strong leader, with the ability to influence across teams and levels.

Work with development teams in an agile context as it relates to software development.

Here’s what will give you an edge…

Provide architectural guidance and technical oversight for AI/ML systems, ensuring solutions are scalable, secure, and production ready.

Drive engineering excellence by championing robust design, peer reviews, and efficient CI/CD practices tailored for AI systems.

Foster strong cross-functional partnerships with Product, Data Science, ML-Ops, and DevOps teams to accelerate delivery and innovation.

Travel Requirement

Limited travel to other company offices upon request

#LI-UB1

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you. 

 Senior Commercial Product Manager - Credit 

The Senior Commercial Product Manager for Credit owns the commercial lifecycle of Billtrust’s credit product portfolio, spanning AI-powered risk assessment, customer credit scoring, and intelligent credit decisioning solutions. This role drives products from ideation through adoption collaborating with internal stakeholders, engineering teams, and directly with customers to define requirements, prioritize the roadmap, and deliver successful go-to-market outcomes. 
 
The ideal candidate is a proactive, natural problem solver who bridges complex technical capabilities and real customer value — and who actively uses AI tools as part of how they work. We’re looking for someone who doesn’t just understand AI as a product category, but who applies it personally: to research, synthesize information, build artifacts, and think through problems faster. This person communicates with clarity and confidence across all settings, from executive 
presentations to customer webinars. 

What You'll Do 

• Own the Credit product portfolio end-to-end — serve as the subject matter expert and primary liaison across revenue, engineering, and customer-facing teams; maintain a prioritized backlog with each sprint aligned to business and customer outcomes 

• Proactively surface gaps and opportunities in the credit workflow before problems escalate, and evaluate incoming feature requests based on market demand, ROI, and customer impact— without needing to be directed 

• Lead external customer presentations, product webinars, and in-person meetings to clearly articulate capabilities, roadmap direction, and ROI; deliver equally compelling internal presentations to senior leadership on product performance, strategic tradeoffs, and investment priorities 

• Own the Credit product scorecard and annual planning baseline — track KPIs including decisioning accuracy, automation rates, and customer health; define tradeoffs and present clear investment options to leadership 

• Build strong client relationships to co-develop capabilities and validate product decisions; partner with Sales and Customer Success on value narratives and enablement content that drive adoption of Credit AI features 

• Collaborate with engineering leads to define requirements, design functionality, and drive 
  delivery from analysis through implementation across a high volume of concurrent initiatives 

• Help shape where and how AI capabilities get embedded into the Credit product — identifying high-value opportunities for intelligent automation, rise decisioning enhancements, and AI-assisted workflows within the product experience 

• Use AI tools as a core part of how you work — synthesizing market signals, accelerating competitive research, drafting PRDs and briefs, and prototyping concepts faster than traditional methods 

• Mentor other product managers and actively share effective AI practices that raise team output quality and speed