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. 

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

• 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

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 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 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

What is the InMobi family like?   

We are an infectious bunch. Be it the way we rise to challenges, the innovative products we create, the dreams we chase or the fun we have at work. We are sure that if you meet us, you will be infected too. Today, we are proud to be the leaders in Mobile advertising and are on an accelerated path of being a leader in enterprise software for marketers. We invite you to free yourself, dream big and chase your passion. We are here today because a few of us did just that.   

What can we promise?   

We offer you an opportunity to work on building enterprise platforms that require you to acquire, hone and demonstrate your ML and AI skills in designing and solving for complex problems, thereby creating software that creates value for our customers in a reliable, scalable, secure, and AI-first manner. At InMobi, you get to work on innovative technologies, work closely with business teams and grow as an overall technology leader.  

Modern work environment, flexible schedule, and smart, creative, down-to-earth people. Internal opportunities to move roles and try out bridge assignments with different teams.  Food for your soul – free meals all days of the week, gym, or yoga class to flex those biceps, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.  

What is the team like?  

At InMobi Enterprise team, we are transforming the way finance, sales, marketing, people, and legal functions operate. We’re driving transformative work across Sales, Marketing, People, and Finance with ML and Agentic AI—and we’re looking for passionate innovators to join us!

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, GenAI and modern agentic AI systems with a strong engineering appetite. You will build and deploy intelligent AI/ML systems that will help transform the business process across the core. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

• Lead the experimentation, design and build of agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Support POCs/ Pilots projects to explore and validate innovative technologies and solutions in ML/AI space.

• Build and operate machine learning models on diverse, high-volume data sources for forecasting, classification and prediction.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Design pipelines for data preparation, model training, evaluation, and deployment in collaboration with engineering counterparts.
• Define best practices for monitoring ML model performance using statistical techniques; identifying drifts, failure modes, and improvement opportunities.
• Contribute to ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
• Document designs, development processes, and best practices to promote knowledge sharing and operational efficiency.

What do we expect from you?

We are seeking candidates with deep expertise in ML and hands-on experience building GenAI and Agentic AI systems.

Skillset: AI/ML Engineering, Python, LLM, RAG, Agentic AI, MCP, REST API

You should have experience with:

• Design, build, and deploy building LLM-powered applications, chatbots, and multi-agent systems to improve efficiency, accuracy, and decision-making.
• Implement and customize GenAI and multi-agent systems using AI frameworks such as LangChain, LangGraph, CrewAI, or similar.
• Create, refine, and maintain prompt templates, chains, and workflows.
• Integrate vector databases (MilvusDB, FAISS, Pinecone, Chroma, etc.) for semantic search and memory.
• Classical ML and deep learning techniques across NLP, clustering, and time series.
• Proficient in deploying ML workflows/models in production system. Continuous monitoring, evaluation, and retraining of models to ensure sustained performance. Ensuring model explainability, accuracy, compliance.
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Stay updated with emerging AI/ML technologies and recommend relevant innovations for the finance domain.
• Drive in design reviews, sprint planning, and technical discussions.
• Collaborating effectively with diverse stakeholders, including technical teams and business leaders.
• Adapting to fast-paced environments and evolving priorities with high energy and autonomy.

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

 Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 8+ years of industry experience in ML/Data Science, with deep proficiency in Python and one or more frameworks: PyTorch, TensorFlow, Scikit-learn.
• Solid understanding of ML fundamentals, regression, tree-based models, clustering, and time series.
• Hands-on experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Experience building Agentic frameworks such as LangGraph, AutoGen, CrewAI, n8n or ReACT-style agents.
• Expertise with algorithms in NLP, Time Series, and Deep Learning, applied on real-world datasets.
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Experience with Model Context Protocols (MCPs) — building or integrating MCP tools, servers, or capabilities.
• Comfortable working in cross-functional teams.
• Strong problem-solving and analytical skills with the ability to work in agile environments.
• Good understanding of data pipelines, APIs, and cloud platforms (Azure/GCP/AWS).
• Excellent communication skills with the ability to simplify complex technical concepts.

What You Will Be Doing

- Design and implement production-ready generative AI applications that serve millions of users, from initial architecture through deployment and monitoring
- Build advanced RAG (Retrieval-Augmented Generation) pipelines that combine vector databases, hybrid search, and intelligent caching to deliver sub-second response times
- Develop multimodal AI systems that seamlessly integrate text, vision, and audio capabilities using state-of-the-art models
- Architect scalable microservices that handle thousands of concurrent AI requests while optimizing for cost, latency, and reliability
- Lead code reviews and technical design sessions, establishing best practices and architectural patterns that elevate the entire team's capabilities
- Optimize large language models through fine-tuning techniques to achieve domain-specific performance improvements
- Implement comprehensive MLOps practices including automated testing, model versioning, A/B testing frameworks, and real-time monitoring dashboards
- Collaborate with product managers and stakeholders to translate complex business requirements into innovative AI solutions
- Deploy AI models across multiple cloud platforms (GCP) using containerization and orchestration technologies
- Create and maintain technical documentation, runbooks, and architectural decision records that enable knowledge sharing across teams
- Mentor junior engineers through pair programming, technical talks, and hands-on guidance to accelerate their growth
- Research and prototype emerging AI technologies to identify opportunities for competitive advantage

Gen AI Responsibilities

- Fine-tune and optimize state-of-the-art language models for specific business use cases, achieving significant improvements in accuracy and relevance
- Design multi-agent AI systems using frameworks to orchestrate complex workflows and decision-making processes
- Implement advanced prompt engineering strategies including Tree of Thoughts, ReAct patterns, and automatic prompt optimization to maximize model performance
- Build production-grade embedding systems that handle billions of vectors, implementing efficient indexing strategies and hybrid search capabilities
- Develop computer vision pipelines using models for tasks ranging from object detection to visual question answering
- Create secure AI applications with robust safeguards against prompt injection, jailbreaking, and data leakage while maintaining compliance with AI governance standards
- Optimize token usage and implement intelligent caching strategies to reduce costs by 50-70% while maintaining quality
- Design and implement evaluation frameworks that go beyond traditional metrics, incorporating human feedback loops and domain-specific quality measures
- Build real-time AI inference systems capable of processing streaming data with sub-100ms latency requirements
- Integrate multiple foundation models into unified applications, implementing fallback mechanisms and load balancing for high availability
- Develop custom tools and functions that extend LLM capabilities, enabling models to interact with databases, APIs, and external systems
- Implement advanced RAG techniques including contextual embeddings, cross-encoder reranking, and Graph RAG for complex reasoning tasks
- Create multimodal search systems that enable users to query across text, images, and documents using natural language
- Build AI-powered data processing pipelines that automatically extract, transform, and enrich unstructured data at scale
- Deploy edge AI solutions using frameworks like ONNX and TensorRT, optimizing models for resource-constrained environments

What We're Looking For

- 5+ years of hands-on experience building and deploying ML/AI systems, with at least 2+ years focused on generative AI and LLMs
- Expert-level Python programming skills with deep knowledge of async programming, multiprocessing, and performance optimization
- Strong experience with modern AI frameworks including PyTorch, Transformers, LangChain, and vector databases
- Proven track record of deploying AI applications to production environments serving real users at scale
- Deep understanding of transformer architectures, attention mechanisms, and the latest advances in generative AI
- Experience with cloud platforms (GCP) and containerization technologies (Docker, Kubernetes)
- Excellent communication skills with the ability to explain complex AI concepts to both technical and non-technical audiences
- Proven experience improving large-scale product search and discovery — including dense retrieval with bi-encoders, cross-encoder reranking, query understanding, and hybrid BM25 + vector search across catalogs of tens of millions of SKUs
- Hands-on experience building and deploying production multi-agent systems using orchestration frameworks such as LangGraph and Google ADK — designing stateful, tool-augmented agents for complex, real-world workflows
- Bachelor's degree in Computer Science, Mathematics, or related field (Master's preferred but not required with relevant experience)

Nice to Have

- Published research papers or significant contributions to open-source AI projects
- Experience with multimodal AI systems combining vision, language, and audio
- Domain expertise in specific verticals (healthcare, finance, legal, e-commerce)
- Knowledge of AI safety, alignment, and constitutional AI principles
- Experience building AI infrastructure and platforms used by other engineers
- Familiarity with emerging technologies like neural architecture search, mixture of experts, or neuromorphic computing

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

At ZoomInfo we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. If you are collaborative, take initiative, and get stuff done we want to talk to you! We have high aspirations for the company and are looking for the right people to help fulfil the dream. We strive to continually improve every aspect of the company and use cutting-edge technologies and processes to delight our customers and rapidly increase revenue. 

Role Overview: ZoomInfo is seeking a Data Analyst III to join the Data Operations and Analysis team. This role partners closely with Product, Engineering, and Research teams to enhance data infrastructure, improve data quality, and deliver actionable insights that drive business impact.

Key Responsibilities:

• Develop a deep understanding of data systems, pipelines, and infrastructure.
• Analyze current data processes, identify gaps, and recommend scalable improvements.
• Drive initiatives to enhance data accuracy, coverage, and efficiency.
• Collaborate cross-functionally with Data Engineering, Product, and Research teams.
• Perform advanced data analysis and present insights in a clear, structured manner.
• Mentor junior analysts and contribute to team capability building.
• Work independently to explore data, propose solutions, and execute projects end-to-end.

Core Competencies:

• Strong analytical thinking and problem-solving ability.
• Ability to work in ambiguous environments and drive clarity.
• Effective communication with both technical and non-technical stakeholders.
• High attention to detail and strong organizational skills.
• Self-driven with the ability to manage multiple priorities.

Required Qualifications:

• 5+ years of experience in analytics, data operations, or quantitative research.
• Advanced proficiency in SQL, Python, BigQuery, and Excel.
• Strong understanding of ETL processes and data quality challenges.
• Experience working with large-scale datasets.
• Familiarity with AI/ML concepts including NLP and data modeling.

Preferred Qualifications:

• Experience building or deploying AI/ML solutions.
• Exposure to tools like Tableau or Looker Studio.
• Experience with Databricks, AWS, or Airflow.
• Background in product-driven or project-based environments.

Impact: This role plays a critical part in shaping the future of ZoomInfo’s data ecosystem by improving data reliability, scalability, and strategic value.

#LI-SG2

#LI-Hybrid

Job Title: Staff Software Engineer, AI

Locations: Bangalore

Reports to: Sr. Manager, AI/ML.

A quick snapshot…

As a Staff Software Engineer, you will be a key contributor to the design, development, and deployment of advanced AI and generative AI-based products. You will drive technical innovation, lead complex projects, and collaborate closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. This role requires a strong background in software development, AI/ML techniques, and DevOps practices, along with the ability to mentor junior engineers and contribute to strategic technical decisions.

Why it’s a big deal…

This is one of the critical roles in the project, where you will be an expert in product development, a good team player, and will lead and mentor your team members. We believe in using the best tools for the task at hand so the ability and desire to learn new programming languages and technologies is necessary. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day. This role determines the root cause for the most complex software issues and develops practical, efficient, and permanent technical solutions.

Are you the person we’re looking for?

Experience: 8+ years of professional software development experience, including significant experience with AI/ML or GenAI applications. Demonstrated expertise in building scalable, production-grade software solutions.

Advanced Software Development: Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability. Drive best practices in code quality, documentation, and test coverage.

GenAI Product Development: Lead end-to-end development of generative AI solutions, from data collection and model training to deployment and optimization. Experiment with cutting-edge generative AI techniques to enhance product capabilities and performance.

Technical Leadership: Take ownership of architecture and technical decisions for AI/ML projects. Mentor junior engineers, review code for adherence to best practices, and ensure the team follows a high standard of technical excellence.

Project Ownership: Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers. Proactively identify and mitigate risks to ensure successful, on-time project completion.

Architectural Design: Contribute to the architectural design and planning of new features, ensuring solutions are scalable, reliable, and maintainable. Engage in technical reviews with peers and stakeholders, promoting a product suite mindset.

Code Review & Best Practices: Conduct rigorous code reviews to ensure adherence to industry best practices in coding standards, maintainability, and performance optimization. Provide feedback that supports team growth and technical improvement.

Testing & Quality Assurance: Design and implement robust test suites to ensure code quality and system reliability. Advocate for test automation and the use of CI/CD pipelines to streamline testing processes and maintain service health.

Service Health & Reliability: Monitor and maintain the health of deployed services, utilizing telemetry and performance indicators to proactively address potential issues. Perform root cause analysis for incidents and drive preventive measures for improved system reliability.

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

Here’s what will give you an edge…

Technical Expertise: Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks. Deep knowledge of software design patterns, object-oriented programming, and concurrency.

Cloud & DevOps Proficiency: Extensive experience with cloud technologies (e.g., GCP, AWS, Azure), containerization (e.g., Docker, Kubernetes), and CI/CD practices. Strong understanding of version control systems (e.g., GitHub) and work tracking tools (e.g., JIRA).

AI/GenAI Knowledge: Familiarity with GenAI frameworks (e.g., LangChain, LangGraph), MLOps, and AI lifecycle management. Experience with model deployment and monitoring in cloud environments.

Preferred Skill sets/Tools:

AI & Machine Learning: Hands-on experience with advanced ML algorithms, including generative models, NLP, and transformers. Knowledge of industry-standard AI frameworks (e.g., TensorFlow, PyTorch) and experience with data preprocessing and model evaluation.

Data & Analytics Tools: Proficiency with relational and NoSQL databases (e.g., MongoDB, MSSQL, PostgreSQL) and analytics platforms (e.g., BigQuery, Snowflake, Tableau). Experience with messaging systems (e.g., Kafka) is a plus.

Testing & Quality: Experience with test automation tools (e.g., PyTest, xUnit) and CI/CD tooling such as Terraform and GitHub Actions. Strong emphasis on building resilient and testable software.

Advanced Cloud Knowledge: Proficiency with GCP technologies such as VertexAI, BigQuery, GKE, GCS, and DataFlow, with a focus on deploying AI models at scale.

#LI-UB1

Title: Senior AI QA Engineer
Location: Bengaluru (Bangalore)

Opportunity:

As a Senior AI QA Engineer for our Precision Patient Care Pipeline, you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies.

Key Responsibilities:

• Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations.
• Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics).
• Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity.
• Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation.
• Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics.
• Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior.

Requirements:

• 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation.
• Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems.
• AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, and custom scoring algorithms). Familiarity with tools like LangSmith, Arize Phoenix, or MLflow.
• Vibe Coding Mastery: Proficiency with AI-native development tools such as Cursor, Windsurf, Claude Code.
• Modern Automation Stack: Proficiency with frameworks like PyTest, and experience with traditional tools (Cypress, Playwright, or Selenium) for end-to-end flows.
• API & Data Testing: Solid understanding of API testing (Postman/RestAssured) and database validation (SQL/NoSQL).
• Strategic Thinking: Experience serving as a Subject Matter Expert (SME) on test process development for large-scale systems.

Preferred (Good to Have):

• Clinical Domain Knowledge: Familiarity with healthcare data standards such as FHIR, HL7, or SNOMED CT.
• Healthcare Compliance: Understanding of HIPAA regulations and the nuances of handling ePHI/PHI.
• Statistical Foundation: Understanding of sensitivity, specificity, and F1-scores in a clinical context.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Title: Senior QA Engineer
Reporting to: Senior Director, Product Development
Location: Bengaluru (Bangalore)

Opportunity:

As a Senior QA Engineer for our Precision Patient Care Pipeline, you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies.

Key Responsibilities:

• Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations.
• Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics).
• Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity.
• Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation.
• Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics.
• Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior.

Requirements:

• 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation.
• Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems.
• AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, and custom scoring algorithms). Familiarity with tools like LangSmith, Arize Phoenix, or MLflow.
• Vibe Coding Mastery: Proficiency with AI-native development tools such as Cursor, Windsurf, Claude Code.
• Modern Automation Stack: Proficiency with frameworks like PyTest, and experience with traditional tools (Cypress, Playwright, or Selenium) for end-to-end flows.
• API & Data Testing: Solid understanding of API testing (Postman/RestAssured) and database validation (SQL/NoSQL).
• Strategic Thinking: Experience serving as a Subject Matter Expert (SME) on test process development for large-scale systems.

Preferred (Good to Have):

• Clinical Domain Knowledge: Familiarity with healthcare data standards such as FHIR, HL7, or SNOMED CT.
• Healthcare Compliance: Understanding of HIPAA regulations and the nuances of handling ePHI/PHI.
• Statistical Foundation: Understanding of sensitivity, specificity, and F1-scores in a clinical context.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities:

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Address:

Bangalore Office  

Tekion India Private Limited 

6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037 

Chennai Office

Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043

Senior Software Architect – Agentic AI & Cloud Platforms

Location: India (Bangalore / Remote Hybrid)
Company: Picarro

Role Overview

Picarro is seeking a highly accomplished Senior Software Architect to lead the design and evolution of our next-generation intelligent platforms. This role sits at the intersection of Agentic AI, cloud-native architecture, and real-time data systems, enabling cutting-edge scientific instrumentation and analytics products.

You will define architectural strategy, guide engineering teams, and build scalable, intelligent systems that integrate AI-driven decision-making with high-throughput data pipelines. This is a hands-on leadership role for someone who thrives in deep technical problem-solving while influencing organization-wide engineering direction.

What You’ll Do

• Architect Next-Gen Platforms:
  Design and scale distributed, cloud-native systems supporting real-time data ingestion, processing, and AI-driven workflows.
• Lead Agentic AI Integration:
  Drive architecture for agent-based AI systems (autonomous decisioning, orchestration, and reasoning frameworks) embedded into core products.
• Own Data & Streaming Architecture:
  Define and optimize event-driven systems leveraging Kafka and streaming pipelines for high-volume, low-latency data.
• Hands-on Technical Leadership:
  Provide deep technical guidance in Java and Python ecosystems, setting best practices for design, performance, and scalability.
• Cloud & Platform Strategy:
  Architect and evolve cloud infrastructure (AWS/Azure/GCP), focusing on resilience, observability, and cost efficiency.
• Cross-Functional Influence:
  Partner with product, hardware, and data science teams to translate complex requirements into scalable software architectures.
• Mentor & Elevate Engineering Talent:
  Coach senior engineers and drive architectural rigor, design reviews, and engineering excellence across teams.

What We’re Looking For

Core Technical Expertise

• 15+ years in software engineering with significant experience in architecting large-scale distributed systems
• Deep expertise in:
• Java (Spring Boot / microservices architecture)
• Python (data pipelines, AI/ML integration)
• Kafka / event streaming platforms
• Strong experience with cloud-native systems (AWS, Azure, or GCP)
• Proven track record building high-throughput, low-latency systems

Agentic AI & Modern Systems

• Hands-on experience or strong exposure to:
• Agentic AI frameworks / LLM-based systems
• Autonomous workflows, orchestration, and reasoning systems
• Familiarity with ML pipelines, model integration, or AI-driven architectures

Architecture & Leadership

• Demonstrated ability to define and drive end-to-end architecture strategy
• Strong system design skills across microservices, APIs, and distributed data systems
• Experience influencing and mentoring senior engineers and tech leads

Nice to Have

• Experience with scientific instrumentation, IoT, or hardware-software integrated systems
• Knowledge of real-time analytics, telemetry, or sensor data platforms
• Exposure to containerization and orchestration (Docker, Kubernetes)
• Background in data engineering or MLOps

• Strong capability to define solution-level data models and end-to-end data architecture spanning analyzers/instrument telemetry, on-prem systems, and cloud software platforms

Why This Role is Compelling

• Work on cutting-edge Agentic AI systems applied to real-world scientific and industrial challenges
• Influence platform architecture at a company level, not just a single product
• Operate at the intersection of hardware, software, and AI
• High visibility role with direct impact on Picarro’s next phase of innovation

About Picarro:

We are the world's leader in timely, trusted, and actionable data using enhanced optical spectroscopy. Our solutions are used in a wide variety of applications, including natural gas leak detection, ethylene oxide emissions monitoring, semiconductor fabrication, pharmaceutical, petrochemical, atmospheric science, air quality, greenhouse gas measurements, food safety, hydrology, ecology, and more. Our software and hardware are designed and manufactured in Santa Clara, California and are used in over 90 countries worldwide based on over 65 patents related to cavity ring-down spectroscopy (CRDS) technology and are unparalleled in their precision, ease of use, and reliability.

At Picarro, we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status, gender identity, social orientation, or disability. Posted positions are not open to third-party recruiters/agencies, and unsolicited resume submissions will be considered free referrals. 

At Picarro, we strive to ensure that all individuals, regardless of their abilities, have equal opportunities. If you are an individual with a disability and require reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, please contact Picarro, Inc. at disabilityassistance@picarro.com for assistance. 

ChargePoint is looking for an AI Engineer who will  design, development, and operation of production‑grade Generative AI systems. You will architect and deliver LLM‑powered applications, including Copilot‑style experiences, AI agents, and automation at enterprise scale.

You will operate with high autonomy, own complex technical initiatives end‑to‑end, and influence GenAI architecture and standards across teams.

Reports To

Senior Manager-Information Security

What You Will Be Doing

As an AI Engineer, you will:

What You Will Bring to ChargePoint

• Proven ability to own ambiguous, complex problem spaces
• Experience influencing architecture and technical direction beyond your immediate team
• Strong system design and debugging skills for distributed AI systems
• Ability to balance speed, quality, and risk in production AI deployments
• Passion for building scalable, maintainable, and responsible AI platforms
• Strong communication skills with engineers, product managers, and leadership

Requirements

• 4 plus years of professional software engineering experience
• Strong development skills in Python (required); experience with Java, Go, or TypeScript is a plus
• Deep hands‑on experience with LLMs and Generative AI systems
• Strong experience with RAG, embeddings, vector search, and prompt engineering
• Experience building Copilot‑style or agent‑based AI systems
• Strong understanding of distributed systems, APIs, and microservices
• Experience deploying and operating systems using Docker/Kubernetes
• Experience with Azure, AWS, or GCP
• Familiarity with LLMOps / MLOps practices

Good to Have

• Experience with AI governance, compliance, or regulated enterprise environments
• Experience with vector databases and retrieval optimization
• Prior ownership of AI systems running in production at scale

Location

Remote location in India

Opportunity

Get Well is seeking a talented and innovative Senior AI Engineer to lead the development and deployment of advanced AI solutions within a mission-driven healthcare environment. This role is ideal for a seasoned professional with hands-on experience in machine learning (ML), large language models (LLMs), and generative AI (GenAI), with a strong focus on productionizing scalable and reliable models.

As a Senior AI Engineer, you will drive end-to-end AI development—from ideation and training data pipelines to model deployment and continuous improvement—while addressing unique healthcare data challenges. You’ll collaborate across functions including product, engineering, data science, and clinical experts to deliver high-impact AI applications, including voice assistants and multimodal systems tailored to real-world care settings.

Responsibilities

AI Model Development & Customization

• Fine-tune SLMs / LLMs and develop ML models for healthcare-specific use cases.
• Build multimodal AI systems that integrate text, structured medical data, and images.
• Optimize models for accuracy, latency, and resource efficiency in production settings.
• Evaluate and integrate speech-to-text (STT) and text-to-speech (TTS) models into conversational interfaces.
• Customize foundation models using domain adaptation and prompt engineering techniques (e.g., PEFT, LoRA).
• Develop AI algorithms from healthcare data and guide them through a full production lifecycle into deployed solutions.

Productionization & Deployment

• Lead model deployment end-to-end with cloud-native tools and infrastructure (Azure ML).
• Implement model performance monitoring, drift detection, and auto-retraining pipelines.
• Ensure AI solutions are scalable, reliable, and aligned with security and compliance requirements in healthcare environments.

Technical Leadership

• Provide technical guidance to junior AI engineers.
• Conduct design reviews and drive the adoption of best practices in model reproducibility, validation, and explainability.
• Lead the evaluation and integration of cutting-edge ML research and open-source frameworks.
• Contribute to architectural decisions aligned with clinical, business, and regulatory goals.

Data Engineering & Management

• Process and curate large-scale, structured and unstructured healthcare datasets.
• Design synthetic data generation strategies where needed to augment training.
• Handle noisy, imbalanced, or incomplete data through robust preprocessing and enrichment.
• Ensure HIPAA and GDPR compliance in data handling, encryption, and access management.
• Leverage EHR and clinical data from the provider side to engineer healthcare data pipelines and training corpora.

Bias Mitigation, Evaluation & Governance

• Lead the creation of robust evaluation strategies combining domain-specific KPIs (e.g., AUC, accuracy) with clinical relevance.
• Proactively identify, measure, and mitigate algorithmic bias, especially in patient-facing models.
• Conduct adversarial stress testing and ensure models meet safety, fairness, and ethical standards.
• Define model KPIs aligned with measurable impacts on clinical outcomes, patient safety, and workflow efficiency.

Cross-Functional Collaboration

• Translate stakeholder and product needs into robust, scalable AI solutions.
• Collaborate with clinical experts to vet model behavior and expected impact in patient and caregiver workflows.
• Participate in Agile processes including sprint planning, demos, and technical retrospectives.
• Manage documentation of model architectures, version changes, testing strategies, and key design decisions.

Learning, Innovation & Thought Leadership

• Stay up-to-date on the latest LLM advancements, STT/TTS developments, voice interaction technologies, and GenAI frameworks.
• Evaluate new models and methods (e.g., RAG, LangChain, Whisper, Tacotron) for their potential impact and feasibility.
• Advocate for responsible AI and lead initiatives in privacy-preserving and explainable ML.
• Contribute to a culture of continuous learning, internal knowledge sharing, and open technical dialogue.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
• Minimum 6+ years of industry experience in AI/ML including at least 2 years with GenAI, NLP/NLU, and LLMs.
• Must have software development experience at a healthcare company, particularly in the provider space (e.g., hospitals, clinical systems) with exposure to EHRs or related healthcare data domains.
• Proven experience developing AI algorithms using healthcare datasets and integrating them into production products or services.
• Experience building voice-enabled products or assistants is highly advantageous.

Technical Skills

• Expert in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with training/fine-tuning LLMs and modern NLP/NLU techniques.
• Hands-on expertise with STT (e.g., Whisper) and TTS (e.g. Elevenlabs) models.
• Proficient in MLOps, including model serving, experiment tracking, container orchestration, and CI/CD pipelines.
• Strong understanding of production-grade solutions using Azure.
• Familiarity with version control (e.g., Git), collaboration tools, and responsible AI practices.
• Familiar with vector databases, retrieval-augmented generation (RAG), and API deployment.
• Comfortable with healthcare regulatory frameworks (e.g., HIPAA, GDPR) and ethical data use policies.

Professional Attributes

• Curious and self-motivated, with a passion for impactful healthcare innovation.
• Effective communicator who can tailor technical concepts to non-technical stakeholders.
• Exceptional problem-solving and quantitative reasoning abilities.
• Team-oriented, growth-minded, and proactive in driving projects forward.
• Highly organized and focused on quality, reproducibility, and compliance.
• Passionate about applying AI to improve outcomes in real-world healthcare systems.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Opportunity

Get Well is seeking a highly experienced and innovative Staff AI Engineer to lead the architecture, development, and optimization of cutting-edge AI solutions across the organization’s healthcare platform. This role requires deep technical expertise in large language models (LLMs), multimodal AI systems, agentic frameworks, and voice technologies—including STT (speech-to-text) and TTS (text-to-speech).

As a Staff-level technical leader, you will guide the AI engineering lifecycle from conceptualization to deployment at scale while serving as a key cross-functional partner to product, engineering, and clinical teams. This is a high-impact, hands-on role for a forward-thinking AI expert with a strong understanding of emerging agentic systems and best practices in safety, observability, and machine learning operations in regulated environments.

Responsibilities

Healthcare-Focused AI System Design & Development

• Architect and develop production-ready AI models trained on real-world clinical datasets sourced from hospital systems, EHRs, and patient engagement platforms.
• Partner with clinical informatics and product teams to derive insights from structured and unstructured health data, including FHIR, HL7, CCDA, and EHR notes.
• Design and train speech-to-text (STT) and text-to-speech (TTS) models to power voice-enabled AI applications and virtual assistants in a healthcare setting.
• Integrate and optimize agentic systems using frameworks such as LangChain, LangGraph, or CrewAI for autonomous decision-making and workflow automation.
• Drive the end-to-end development lifecycle—from data prep and model training to evaluation, deployment, and monitoring—ensuring responsiveness and efficiency in high-impact healthcare settings.
• Evaluate and incorporate emerging AI technologies and architectural tools to improve intelligence, personalization, and user experience.

Infrastructure Optimization & MLOps

• Lead the model lifecycle from ingestion and preprocessing of healthcare datasets (e.g., EHR records, patient surveys, clinical measurements) to training, evaluation, and deployment into hospital IT ecosystems.
• Lead the design and optimization of cloud-based AI infrastructure, focusing on scalability, performance, observability, and cost-efficiency (Azure preferred).
• Establish and maintain scalable CI/CD pipelines, GPU-optimized runtimes, and real-time or batch inference systems in Azure healthcare-compliant environments.
• Ensure reliability, production-grade observability, and rollback safeguards using tools like Langfuse, Prometheus, Grafana, and other internal tools.

Monitoring, Observability & Reliability

• Set up and manage observability tools and frameworks such as Langfuse, Prometheus, Grafana, or equivalent to monitor operational health of AI models and agentic workflows.
• Establish proactive monitoring for model performance, agent behavior, anomaly detection, and feedback loop management.
• Rapidly diagnose and address system bottlenecks, drift, or failure points in production environments.

Healthcare Compliance & Responsible AI

• Ensure all AI solutions adhere to HIPAA, GDPR, and internal privacy and data security standards.
• Design and enforce ethical AI principles, focusing on bias mitigation, explainability, reproducibility, and accountability.
• Oversee secure handling and governance of sensitive data, including ePHI and PHI, in compliance with Federal, State, and local regulations.

Cross-Functional Collaboration & Technical Leadership

• Act as a principal technical liaison between AI engineering, product, design, and clinical stakeholders.
• Translate complex technical architectures into product-aligned features and user-centric outcomes.
• Collaborate closely with clinical experts to ensure AI solutions address high-impact, evidence-based healthcare needs.
• Mentor and elevate junior engineers through architecture reviews, hands-on pairing, and code quality leadership.
• Drive a culture of innovation, excellence, and learning across AI engineering and data science teams.

Qualifications

Education & Experience

• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related technical field.
• 8–10+ years of hands-on experience in AI/ML development, with 3+ years in technical leadership or Staff/Principal-level roles.
• Proven track record of delivering production-grade AI systems in healthcare industries.

Technical Expertise

• Deep expertise in:
  • LLMs (e.g., OpenAI, LLaMA, Claude) and transformer-based NLP models
  • Multimodal learning architectures integrating text, image, and structured healthcare data
  • Fine-tune SLMs / LLMs and develop ML models for healthcare-specific use cases.
  • Agentic AI systems using frameworks like CrewAI, LangChain, and LangGraph
  • STT/TTS models (e.g., Whisper, Tacotron, FastSpeech, DeepSpeech)
• Advanced programming in Python (required); familiarity with C++ is a plus.
• Proficient in AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, and model serving stacks.
• Hands-on experience with MLOps frameworks, infrastructure-as-code, container orchestration, and model registries.
• Familiarity with healthcare data standards (FHIR, HL7, SNOMED, ICD-10) and clinical integration best practices
• Awareness of cutting-edge trends in Agentic Systems, Multimodal Context Processing (MCP), A2A (Agent-to-Agent) protocols, and healthcare-centric AI safety practices.

Professional Attributes

• Strong analytical and problem-solving abilities with a bias for action.
• Excellent communicator—able to translate complex AI systems to diverse stakeholders.
• Proven ability to work in fast-paced, cross-functional, and agile product environments.
• Committed to high standards of privacy, compliance, and ethical AI.
• Demonstrated experience mentoring engineers and influencing platform and product direction through thought leadership.
• Adaptability to rapid technological shifts and emerging AI frameworks.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About the Role:

The HR Operations Manager role is an IC and hybrid position that delivers both operational HR support and HRIS systems administration within ABBYY’s global People Shared Services team. The role provides employee and manager support, ensures consistent application of People policies across assigned regions, and contributes to efficient, compliant employee lifecycle processes.

In parallel, this position supports the configuration, optimization, and maintenance of our core People systems, HiBob (HRIS) and Greenhouse (ATS), and plays a key role in maintaining data accuracy, improving workflows, and enabling reliable People data reporting.

This role is ideal for someone who enjoys solving problems, improving processes, and working at the intersection of People Operations and HR technology in a global, fast-paced environment.

Job Responsibilities:

People Operations Support

• Provide regional People Operations support for an assigned geography within the global People Shared Services team.
• Ensure global People policies and workflows are applied appropriately within the region, accounting for local compliance requirements.
• Respond to employee and manager inquiries through our case management system (AskABBYY), meeting all SLAs with timely, accurate, and high-quality support.
• Process global HR lifecycle transactions, including onboarding, job changes, compensation adjustments, leaves, and offboarding.
• Maintain employee data in our People systems of record through validation, updates, and reconciliations.
• Partner cross-functionally to ensure coordinated employee lifecycle support.

HRIS and ATS Systems Administration (HiBob and Greenhouse)

• Support configuration and ongoing management of HiBob (HRIS) and Greenhouse (ATS), including workflows, permissions, automations, custom fields, templates, and lifecycle processes.
• Translate business requirements into technical system changes, implementing enhancements and new features as needed.
• Troubleshoot system issues and partner with internal teams or vendors to resolve them.
• Serve as a knowledgeable resource on system functionality, best practices, and platform capabilities.

Data Quality, Reporting & Analytics

• Ensure accuracy and integrity of employee data across all People systems.
• Conduct data audits and reconciliations and resolve discrepancies.
• Support the creation and maintenance of scheduled and ad hoc People data reports and dashboards.
• Address data integration issues between People systems and downstream systems such as payroll, IT, or Finance tools.

Process & Documentation Support

• Create and maintain SOPs, workflows, system documentation, and user guides.
• Document system configurations and data processes to ensure clarity and consistency.
• Identify opportunities for process improvement, automation, and standardization across regions.
• Ensure all documentation reflects current policies, systems, and operational practices.

Job Requirements:

• 6+ years of experience in People Operations, HR Operations, HRIS administration, or a similar hybrid role.
• Experience with HiBob (or another modern HRIS) and Greenhouse strongly preferred.
• Solid understanding of HR processes and the employee lifecycle.
• Experience supporting global or multi-country populations.
• Strong analytical skills, including reporting or data interpretation experience.
• High level of accuracy and attention to detail.
• Ability to translate business needs into system or operational requirements.
• Strong customer service orientation and ability to provide timely, helpful support.
• Effective communication and cross-functional collaboration skills.

Here are some of our local benefits:

• Comprehensive medical, accidental, and life insurance
• Weekly wellness sessions to support your physical and mental well-being
• A generous paid time off policy

#LI-MM1

Glean is looking for engineers to help build the world’s best search and assistant product for work. Our engineers work on a range of systems across the stack, including query understanding, document understanding, domain-adapted language models, natural language question-answering, evaluation, and experimentation. We interact regularly with customers, deeply understand their pain points, and use whatever tool is necessary, simple or complex, to solve their problems.

You will:

• Invent new signals to improve the personalization of our search engine
• Train a model to capture interactions between signals in our ranking system
• Design smarter ways to domain-adapt language models to each customer’s corpus
• Discover new ways of combining LLMs with search engines to answer complex questions
• Write robust code that’s easy to read, maintain, and test
• Mentor more junior engineers, or learn from battle-tested ones

About you:

• 6+ years of experience
• BA/BS in computer science, math, sciences, or a related degree
• Experience working with search, recommendation, natural language processing, or other large systems involving machine learning
• Strong analytical skills and ability to work with data
• Proven ability to design, build, and ship production-ready models
• Proficiency in your ML framework of choice
• Strong coding skills (Python, Go, Java, C++, ...)
• Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company is a must
• A proactive and positive attitude to lead, learn, troubleshoot and take ownership of both small tasks and large features

Location: 

• This role is in person in Bangalore, India

Compensation & Benefits:

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

About Netradyne:

Netradyne provides AI-powered technologies for fleet management and safer roads. An award-winning industry leader in fleet safety and video telematics solutions, Netradyne empowers thousands of commercial fleet customers across North America, Europe, and Asia to enhance their driver performance, reduce risk, and optimize operations.

Netradyne sets the standard among transportation technology companies for enhancing and sustaining road safety, with an industry-leading 25+ billion miles vision-analyzed for risk and an industry-first driver scoring system that reinforces safe behaviors. Founded in 2015, Netradyne is headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. For more details visit: www.netradyne.com

Job Overview:

As a Staff Data Engineer – ML at Netradyne, an award-winning industry leader in fleet safety and video telematics solutions, you will take senior technical ownership of the machine learning and data platforms that underpin our AI-powered fleet analytics. This role is responsible for designing, building, and scaling production-grade ML pipelines, generative AI capabilities, and real-time data streaming systems across cloud and edge environments, delivering actionable insights that make fleet operations safer and more efficient. You will collaborate closely with machine learning engineers, data scientists, and product teams to integrate advanced AI technologies into Netradyne's platform, including on-device edge intelligence and natural-language-driven capabilities. Your work will directly shape the data infrastructure behind Netradyne's Physical AI vision, where AI continuously interprets multimodal vehicle data to understand drivers, vehicles, and road environments as an integrated system.

Key Responsibilities:

• You will be embedded within a team of machine learning engineers and data scientists, responsible for building and productising generative AI, deep learning, and data engineering solutions. You will:
• Design, develop and deploy production-ready, scalable solutions that utilise generative AI, traditional ML models, data science workflows, and ETL/ELT pipelines on AWS cloud infrastructure (and hybrid edge-cloud environments).
• Build and manage real-time and batch data streaming pipelines to handle high-volume, high-velocity data from fleet devices, leveraging technologies such as Apache Kafka and Amazon Kinesis for low-latency processing and near real-time insights.
• Collaborate with cross-functional teams (Product, Data Science, ML Engineering, Operations) to integrate AI-driven solutions into business operations and customer-facing products.
• Design and implement generative AI solutions using large language models (LLMs), including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) patterns, to enable intelligent analytics, natural-language interfaces, and context-aware insights across fleet and safety data.
• Build and scale agentic AI systems by developing autonomous and semi-autonomous agents that orchestrate data retrieval, reasoning, and actions across ML pipelines and services, ensuring these agentic workflows are production-grade, observable, and aligned with safety, reliability, and governance requirements.
• Implement MLOps best practices including CI/CD pipelines for model training, automated testing, model versioning, continuous monitoring, and modern workflow orchestration (e.g. Apache Airflow, MLFlow) to achieve reliable, reproducible model deployments at scale.
• Champion data quality and governance by implementing data contracts, rigorous validation, and monitoring to ensure that analytical pipelines meet defined SLAs and that downstream models and business users can trust the data.
• Conduct research and stay current with the latest advancements in generative AI, vector search techniques, LLM frameworks, orchestration platforms, and related technologies.

Mandatory Skills:

• Experience with data visualisation and BI tools (e.g. Tableau, Grafana, Plotly Dash).
• Exposure to real-time data streaming and messaging systems (e.g. Apache Kafka, Amazon Kinesis, Amazon SQS).
• Knowledge of containerisation and orchestration (e.g. Docker, Kubernetes/EKS)
• Strong understanding of generative AI system design, including prompt engineering, RAG architectures, vector search, and evaluation techniques for LLM-based applications in production environments.
• Experience with agentic AI patterns, such as designing, orchestrating, and monitoring autonomous or semi-autonomous agents that coordinate tools, data sources, and ML services with appropriate safety, observability, and governance controls.
• Experience with modern workflow orchestration platforms such as Apache Airflow, Prefect, or Dagster for scheduling and managing complex ETL/ML pipelines. These tools are now standard for data pipeline engineering.
• Proficiency with at least one Python web framework (e.g. FastAPI, Django, Flask) for developing data or model-serving APIs.
• Experience with rapid prototyping tools (e.g. Streamlit, Gradio, Dash) for demonstrating ML solutions to stakeholders.
• Familiarity with modern ML frameworks and libraries such as PyTorch, TensorFlow, and Hugging Face Transformers
• Background in large-scale data processing and lakehouse or data warehousing technologies (e.g. Snowflake, Amazon Redshift, Apache Spark/EMR, Delta Lake).

Qualifications and Education Requirements:

• B.Tech, M.Tech or PhD in Computer Science, Data Science, Electrical Engineering, Statistics, Mathematics, Operations Research, or a related field (or equivalent professional experience).
• 5–8 years of industry experience in data engineering, machine learning engineering, or related roles, with a track record of building and scaling data/ML solutions in production.
• Strong programming skills in Python and SQL, with solid fundamentals in algorithms, data structures, and object-oriented programming.
• Experience building end-to-end solutions on AWS cloud infrastructure including developing data pipelines (ETL/ELT), deploying ML models at scale, and utilising cloud services (e.g. S3, Lambda, EKS).
• In-depth understanding of data storage systems: proficient with relational databases (SQL), NoSQL datastores, and modern vector databases, including schema design and query optimisation for large-scale datasets.
• Hands-on experience with generative AI tools and workflows, and practical work with large language models (LLMs), including building LLM-powered applications and utilising RAG techniques to incorporate external knowledge.
• Working knowledge of MLOps principles and tools — e.g. model lifecycle management, CI/CD pipelines for ML, automated data/feature pipelines, and monitoring/alerting for deployed models.
• Strong analytical and problem-solving skills with keen attention to detail.
• Solid foundation in statistics, probability, and estimation theory.
  
  

Equal Opportunity Employer Statement:
Netradyne is an equal opportunity employer and are committed to creating an inclusive environment for all employees.

About the role:

The Talent Acquisition Specialist will lead sourcing, attracting, and hiring top talent across the APAC region, leveraging advanced proficiency in Greenhouse ATS and LinkedIn Recruiter. The ideal candidate will bring deep knowledge of APAC talent markets, a proven ability to hire across diverse functions, and expertise in managing a data‑driven, end‑to‑end recruitment process. This role requires a collaborative, strategic partner who excels in stakeholder alignment and delivering an exceptional candidate experience. 

Job Responsibilities: 

Recruitment Strategy & Execution 

• Drive the full-cycle recruitment process across India and the broader APAC region using Greenhouse ATS for requisition management, candidate tracking, pipeline updates, interview workflows, and reporting. 

• Partner closely with hiring managers to deeply understand hiring needs, role requirements, and business objectives across technical and non‑technical functions. 

• Leverage LinkedIn Recruiter, direct sourcing, talent mapping, job boards, referrals, and market insights to attract high-quality active and passive candidates. 

• Build and maintain robust talent pipelines for priority and high‑growth roles across multiple APAC markets. 

Stakeholder Management & Collaboration 

• Collaborate with hiring managers and HR business partners to define recruitment strategies, hiring timelines, and selection criteria. 

• Provide consistent, data-driven updates through Greenhouse dashboards and reports, including talent availability, salary data, and competitive market trends. 

• Serve as a trusted advisor to business leaders, guiding them on recruitment best practices, market shifts, and talent trends across APAC. 

Candidate Experience 

• Ensure a seamless and positive candidate experience by managing all touchpoints through Greenhouse and maintaining timely, transparent communication. 

• Conduct candidate engagement throughout the interview cycle, including expectations setting, interview prep, and feedback delivery. 

• Champion the company’s culture and values to create a compelling and consistent employer narrative. 

Market Research & Talent Sourcing 

• Conduct talent and compensation benchmarking within India and APAC using market research, sourcing insights, and Greenhouse pipeline analytics. 

• Develop innovative sourcing strategies, tapping into LinkedIn Recruiter Projects, talent intelligence data, and community networks to attract diverse talent pools. 

• Represent the organization at virtual career fairs, networking sessions, and recruitment events to grow employer visibility across APAC. 

Process Improvement & Reporting 

• Track, analyze, and report on recruitment KPIs (time-to-fill, funnel conversion rates, source effectiveness) using Greenhouse reporting and dashboards to drive continuous improvement. 

• Ensure full compliance with India and APAC labor laws, internal controls, and hiring policies. 

• Regularly optimize hiring processes, interview structures, and workflows within Greenhouse to increase efficiency and quality of hire. 

Employer Branding & DEI 

• Support employer brand initiatives across India and APAC, leveraging hiring data and market insights to improve brand positioning. 

• Promote and champion diversity, equity, and inclusion throughout the recruitment process, ensuring diverse, representative talent pipelines. 

• Participate in university hiring, brand activations, and diversity-focused sourcing events. 

Job Requirements: 

Education 

• Bachelor’s degree in Human Resources, Business Administration, or related field.  

Experience 

• 5+ years of talent acquisition experience across India and APAC with proven success recruiting in fast‑paced, high‑growth environments. 

• 3+ years of using Greenhouse ATS & LinkedIn recruiter 

• Extensive hands‑on experience with Greenhouse ATS, including workflow configuration, interview scheduling flows, reporting, scorecards, structured hiring, and bulk process management. 

• Advanced LinkedIn Recruiter skills, including pipeline building, market mapping, Boolean sourcing, and outreach sequencing. 

• Experience hiring across multiple job families (technology, engineering, sales, business operations). 

• Strong understanding of regional labor markets, cultural nuances, and hiring regulations across APAC. 

Skills 

• Excellent interpersonal and communication skills, with the ability to influence and build strong relationships with hiring managers and candidates. 

• Strong organizational skills and the ability to manage multiple priorities simultaneously. 

• Deep expertise in sourcing strategies, recruitment marketing tools, and talent intelligence. 

• Passion for DEI, with demonstrated success recruiting diverse talent. 

• Fluency in English (written and verbal). 

Here are some of our local benefits:

• Comprehensive medical, accidental, and life insurance 

• Weekly wellness sessions to support physical and mental well‑being 

• Generous paid time off policy 

This is a hybrid role requiring at least two days per week onsite at our Bangalore office. 

#LI-MM1

About the role:

We are looking for a Staff Software Engineer to help build and scale ABBYY’s AI platform. This role sits at the intersection of platform engineering, MLOps, and DevOps. You will own how AI services are built, deployed, observed, and evolved in production, with a strong focus on Kubernetes, cloud infrastructure, and ML lifecycle automation.

This is a hands-on technical leadership role. You will design systems, write production code, influence architecture, and mentor engineers.

Job Responsibilities: 

• Design and build scalable AI platform services using Python and microservice architectures
• Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback
• Build and maintain Kubernetes-based platforms for AI workloads
• Work on data pipelines, dataset versioning, and auto-labeling workflows for model training
• Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring
• Collaborate closely with ML researchers, product teams, and other platform engineers
• Drive best practices in software design, reliability, security, and observability
• Lead technical discussions, review designs, and mentor team members

Job Requirements:

• 10+ years of experience in backend or platform engineering
• Strong proficiency in Python (or similar backend languages)
• Solid experience building microservices and distributed systems
• Hands-on expertise with Kubernetes in production environments
• Strong understanding of DevOps and MLOps principles
• Experience with data management for ML (datasets, labeling, pipelines)
• Cloud experience with Azure or strong willingness to adopt Azure quickly
• Ability to think at system level and still deliver hands-on

Nice to have:

• Experience building internal AI/ML platforms
• Familiarity with model serving frameworks and inference optimization
• Exposure to auto-labeling, weak supervision, or human-in-the-loop systems
• Experience in enterprise or B2B SaaS environments

Here are some of our local benefits:

• Comprehensive medical, accidental, and life insurance 

• Weekly wellness sessions to support physical and mental well‑being 
• Generous paid time off policy 

#LI-MM1

About the role:

ABBYY is seeking an HR Systems Analyst to design, optimize, and scale systems that power the global employee lifecycle. This role sits at the intersection of People, Data, and Operations, ensuring a seamless, data-driven employee experience. 

You will own and integrate our core People tech stack (HiBob, Greenhouse, SharePoint, Power BI), transforming them into a unified, efficient system that drives automation, accuracy, and insight across the organization. 

Job Responsibilities:

HR Systems Ownership

• Manage and optimize HiBob, Greenhouse, and related tools  

• Ensure data integrity, security, and system performance  

• Drive adoption and continuous improvement 

Workflow & Automation

• Design scalable workflows across hiring, onboarding, employee changes, and offboarding 
• Automate processes using Power Automate and native tools to reduce manual work 

Systems Integration

• Own integrations across HR, Finance, and IT systems (e.g., payroll, NetSuite)  
• Manage APIs and data flows to maintain a single source of truth 

Data & Reporting

• Build Power BI dashboards for workforce insights  

• Track key metrics (hiring, headcount, attrition, performance)  

• Deliver actionable insights to leadership  

1. Process Standardization

• Translate business needs into scalable system solutions  

• Establish global standards while supporting local flexibility 

Job Requirements:

• 4–7+ years in HRIS / People Systems roles 
• Experience with HiBob (or similar HRIS) and Greenhouse (or ATS) 
• Strong skills in SharePoint, Power BI, and workflow automation
• Experience with APIs, integrations, and data pipelines
• Proficiency in Excel; SQL preferred
• Strong problem-solving and system-thinking mindset 

Here are some of our local benefits:

• Comprehensive medical, accidental, and life insurance
• Weekly wellness sessions to support your physical and mental well-being
• A generous paid time off policy

#LI-MM1

About the Role:

We are seeking an energetic and detail-oriented Demand Marketing Specialist to join our APAC marketing team on an 8-month maternity cover contract. In this role, you will play a critical part in driving demand generation efforts across the region, supporting the end-to-end execution of marketing campaigns, events, and other initiatives. If you thrive in a fast-paced environment, have a keen eye for detail, and are passionate about delivering high-quality marketing programs, we’d love to hear from you.

Job Responsibilities:

• Event Management:
• Plan, coordinate, and execute ABBYY Ascend, 3rd party events, industry tradeshows, and webinars, ensuring alignment with overall business and marketing objectives.
• Manage all event logistics, vendor coordination, speaker coordination, platform setup, post-event follow-up and on-site/off-site support to ensure seamless execution.
• Collaborate with internal teams to align event goals with broader marketing objectives.
• Track and analyze webinar performance to optimize future sessions.

• Campaign Execution:
• Support end-to-end execution of integrated email campaigns, including creating internal campaign briefs, content creation and performance tracking.
• Collaborate with cross-functional teams to develop high-impact campaign assets that are compelling, on-brand, and tailored to the unique needs of the APAC audience.
• Develop clear and concise campaign briefs for internal and external stakeholders.

• Vendor & Invoice Management:
• Manage relationships with external vendors, ensuring timely delivery of services and adherence to agreed-upon terms.
• Process invoices and ensure accurate tracking of marketing expenses, adhering to internal financial processes and timelines.
• Work closely with the finance team to ensure budget alignment and resolve any invoicing discrepancies.

• Performance Tracking & Reporting:
• Monitor and report on the performance of campaigns and events, providing actionable insights to improve ROI.
• Use data-driven approaches to optimize marketing efforts and achieve demand generation goals.

• Collaboration:
• Partner with cross-functional teams, including revenue, marketing operations, product marketing and external agencies to ensure alignment and successful execution of marketing initiatives.

Job Requirements:

• Experience:
• 7+ years of experience in demand generation, event marketing, or a related marketing role, preferably within the IT or software industry.
• Proven track record of managing events, campaigns, and webinars end-to-end.
• Skills:
• Strong project management and organizational skills with the ability to manage multiple priorities simultaneously.
• Excellent written and verbal communication skills.
• Proficiency in marketing tools and platforms (Salesforce, Zoom, Jasper & Hubspot).

• Attributes:
• Self-starter with a proactive approach to problem-solving.
• Meticulous and detail-oriented, committed to delivering high-quality work.

This is a 6 to 8 months contract role covering maternity leave.

#LI-MM1

Title: QA Engineer

Reporting to: Director, QA Engineering
Location: Bengaluru (Bangalore)

Opportunity:

We are seeking a skilled AI QA Engineer with 4–6 years of experience in test automation and a strong focus on validating AI/ML and LLM-based systems. The ideal candidate will have hands-on expertise in automation frameworks, API/UI testing, and experience in validating NLP/LLM models across complex, data-driven applications.

Key Responsibilities

• Design, develop, and maintain scalable automation frameworks for UI, API, and backend systems
• Perform end-to-end testing of AI/ML pipelines, including NLP and LLM-based applications
• Validate LLM outputs using techniques such as prompt validation, response scoring, and model comparison
• Build and execute test strategies for microservices and event-driven architectures
• Conduct data validation across systems using SQL/BigQuery and ensure data accuracy in pipelines
• Automate regression, smoke, and end-to-end test suites to improve coverage and efficiency
• Integrate automated tests into CI/CD pipelines using Jenkins or similar tools
• Collaborate with developers, data scientists, and product teams to ensure high-quality AI solutions
• Analyze defects, identify root causes, and ensure timely resolution
• Continuously improve test frameworks, tools, and processes

Required Skills & Qualifications

Automation & Testing

• Strong experience in Selenium WebDriver, RestAssured, TestNG
• Expertise in API Testing, UI Testing, and Microservices Testing
• Experience in building Hybrid/POM-based automation frameworks

Programming

• Proficiency in Java (mandatory)
• Basic working knowledge of Python

AI / ML / LLM Testing

• Experience testing NLP/LLM models (e.g., BERT, GPT-based models, QWEN, Gemini)
• Knowledge of NER validation, prompt testing, and output evaluation techniques
• Exposure to model validation, scoring mechanisms, and dataset validation

Data & Cloud

• Strong SQL skills with experience in BigQuery or similar platforms
• Understanding of event-driven systems (Pub/Sub or similar)
• Experience in validating JSON-based data pipelines

DevOps & Tools

• Experience with Jenkins, Maven, Git/Bitbucket
• Knowledge of CI/CD pipeline integration and test reporting (Allure or similar)

Good to Have

• Experience in Healthcare, OTT, or E-commerce domains
• Exposure to EMR/EHR systems or clinical data validation
• Knowledge of UMLS, CUI mapping, or healthcare NLP concepts
• Experience with mobile testing (Appium)

Experience

• 4–6 years of experience in QA Automation / SDET roles
• Hands-on experience in AI/ML or LLM validation is highly preferred

Education

• Bachelor’s degree in Engineering, Computer Science, or related field

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

The Opportunity

Search Team at Postman is responsible for enabling users to quickly find and get started with the APIs that they are looking for. Postman is growing at a rapid pace, and this manifests into an ever-increasing volume of data that users create and consume, within their teams and in the Public API Network. We focus on improving discovery and ease of consumption over this data.

We are looking for a Senior Engineer with 6+ years of experience deep backend expertise on search and ETL systems and a strong product mindset, to lead core initiatives on our search platform. In this role, you'll work at the intersection of infrastructure, relevance, and developer experience—designing systems that power search across the platform. You’ll bring a bias for action, a strong backend foundation, and the curiosity to explore beyond traditional boundaries, including areas like high performance web services, high volume data pipelines, machine learning, and relevance tuning.

What You'll Do

• Own end to end architecture and roadmap of search platform consisting of distributed indexing pipelines, storage infra and high performance web servers.
• Contribute to improving relevance of search results through signal engineering and better data models.
• Keep the system performant and reliable to handle growing data volume and query traffic, while unblocking business requirements and managing risk.
• Collaborate with cross-functional stakeholders like Product Managers, Designers, as well as other teams to drive initiatives.
• Uphold operational excellence in the team, showing a bias for action and user empathy.
• Quickly build functional prototypes to solve internal and external use-cases.
• Scale the technical abilities of engineers in the team and uphold quality through code reviews and mentorship.

About You

• You have 6+ years of experience building applications in high level programming languages - Javascript, Python, Java etc. We code primarily in Python and Javascript.
• You have worked on customer facing search solutions and have hands-on experience with search systems like ElasticSearch/Apache Solr/OpenSearch.
• Experience building systems to orchestrate batch and streaming pipelines using Apache Kafka, Kinesis, Lambdas. Knowledge of compute engine/data processing engine like Apache Spark/ Apache Flink/ Ray.
• You have displayed strength in AI, Natural Language Processing, Ranking Systems or Recommendation Systems.
• You possess strong Computer Science fundamentals - Algorithms, Networking and Operating Systems, and are familiar with various programming tools, frameworks, and development practices.
• You write testable, maintainable code with SOLID principles that’s easy to understand.
• You are an excellent communicator who can articulate technical concepts to product managers, designers, support and other engineers.

About Enterpret 

Enterpret is at the forefront of AI-native applications, unlocking the power of customer feedback for businesses. We centralize feedback from every channel and transform it into actionable insights that drive customer-centric decisions for teams at the world's leading companies like Perplexity, Notion, Canva, and Figma. Backed by investors such as Kleiner Perkins and Peak XV, we're redefining how businesses understand and act on the voice of their customers.

Read more about our team, core values, and operating principles - here.

What You’ll Do ?

• Build and scale core backend systems that power our customer feedback intelligence platform.
• Take ambiguous product problems and turn them into clear backend systems with strong data and correctness guarantees.
• Own critical system decisions around data models, event flows, and service boundaries.
• Build and harden ML and NLP infrastructure so features work reliably in real customer environments.
• Balance speed, cost, and long-term system health while shipping continuously.
• Instrument systems deeply to detect failures early and learn from production behaviour.
• Influence technical direction by identifying leverage points and proposing platform-level improvements.

What It Takes ?

• 1-3 years in software engineering, with a proven record of building and shipping reliable systems
• Proven ability to design and ship backend systems that operate at scale and stay reliable in production.
• Strong systems thinking: you reason clearly about data models, boundaries, failure modes, and tradeoffs.
• Track record of owning complex projects end to end, from problem framing to production impact.
• Comfort working in ambiguity and making decisions with incomplete information.
• Depth in at least one core backend or infra area and the ability to go deep when things break.
• High engineering judgment: you know when to move fast and when to slow down.
• Strong product sense: you understand how technical decisions affect users and business outcomes.
• Obsession with quality, correctness, and long-term maintainability.
• Ability to influence and raise the bar through code, reviews, and mentorship.
• Bias toward action, learning, and continuous improvement.

Why Enterpret?

• High Impact: Build foundational systems at an early-stage startup where every line of code matters.

• Ownership: End-to-end responsibility for features and systems.

• Complex Challenges: Work on state-of-the-art ML platforms, distributed infra, and real-time analytics.

• Growth: Learn and grow with a high-caliber team and expand into leadership or deep technical expertise.

• Culture: Open, collaborative, and values-driven environment with autonomy.

• Benefits: Competitive salary, equity, premium healthcare, and more.

What We Value ?

At Enterpret, we operate with a deep sense of ownership - we play for the team and do what it takes to win together. We care personally for our teammates while pushing each other with honest, actionable feedback. Above all, we approach everything with humility and a drive to keep learning and getting better.

Equal Opportunities

We are an equal opportunity employer. We ensure that none of our employees or prospective employees receives less favourable treatment as a result of age, sex, disability, marital status, colour, race, religion or ethnic origin. Equally we aim to ensure that no such employee is disadvantaged by terms and conditions of employment which cannot be justified.

The Community You Will Join: 

The Analytics Centre of Excellence (ACOE) at Airbnb, based in India, is a hub of knowledge and expertise that aims to provide data-driven decision-making, enabling Airbnb's business goals. The ACOE's vision is to build a world-class analytics organization that provides scalable analytics. We work with various business functions such as payments, trust, digital, customer support, hosting, sales, social, compliance, risk, platforms and partnership & economics.

The ACOE's delivery framework is designed to provide relevant and contextual insights for data-driven decisions. This includes a one-stop solution for metrics, dashboards driving actionable insights, optimisation of performance, measuring pre/post feature impact, sizing the ROI of opportunities, prioritisation of opportunities, anomaly-driven alerting mechanisms, root cause analysis of metric deviation, and exploratory hypothesis testing.

We are looking for a hands-on lead advanced analyst  who has demonstrated success in building an analytics team with functional expertise in building analytical solutions. Be a trusted partner to product teams and business leaders, across marketplace teams through providing insights, recommendations, and enabling data driven decisions. This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS organization.

The Difference You Will Make:

• Data thought partner to product and business leaders across marketplace teams through providing insights, recommendations, and enabling data informed decisions.  
• Drive day to day product analytics and build scalable analytical solutions
• Develop a deep understanding of how guests and hosts interact with our CS products including but not limited to AI Assistant, IVR and other agent assisting tools to improve the customer experience.

A Typical Day: 

• Owning the product analytics roadmap, prioritisation & delivery of solutions in the Contact Center Product space. 
• Own projects from start to end: building out timelines, key milestones, providing regular updates to product managers, analytics management and delivery against agreed timelines.
• Lead end-to-end measurement for AI systems, aligning metrics with business outcomes, user experience, and trustworthiness
• Collaborate with engineering to define scalable logging and ensure observability across agentic and LLM workflows.
• Lead the design and evaluate A/B and causal tests to quantify impact of AI features and optimisations.
• Translate insights into strategic recommendations for senior leaders; shape product priorities through data.
• Hire, mentor and up-level team capability in AI analytics, experiment best practices and storytelling.
  
  

Your Expertise:

• Min 8 or more years in industry experience and a degree (Masters or  PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
• Expert communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment. Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences
• Strong expertise in Python, SQL, A/B testing platforms and best practices
• Expertise in EDA, hypothesis testing, significance testing, regression, clustering techniques, concepts of NLP/Text Mining, machine learning and deep learning techniques, language model fine-tuning etc
• Understanding of LLM architectures (e.g., prompt chains, retrieval augmentation, orchestration frameworks like LangChain or DSPy).
• Data engineering foundations, including ability to work with data engineering teams on pipeline design, metric computation jobs, data model changes, and maintaining reliable end-to-end metric systems
• Familiarity with Agentic AI systems, human-in-the-loop design, and AI observability best practices
• Experience partnering with internal teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurement.
• Experience designing and building metrics, from conception to building prototypes with data pipelines
• Familiarity with vector stores, embeddings, prompt instrumentation, and structured logging of LLM interactions would be a plus
• Contact center domain and market place domain knowledge would be a plus

Our Commitment To Inclusion & Belonging: 

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 6+ years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 
• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 
• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency
• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

Overview

You will join the Sailfin Accounts Receivable (AR) Team, a product engineering team working in the Finance and Accounting domain. The team designs, develops, deploys, and maintains a large-scale AR product used by global customers. Most of the team is based in India, including this role in Bangalore, and we work with a modern technology stack—AI/ML models, LLMs, multi-agent systems, cloud platforms, and automation frameworks. Our focus is on building secure, scalable, and intelligent solutions that transform financial operations.

The Role

We are looking for an Applied AI Engineer who can build production-ready predictive, generative, and agentic AI solutions for the Finance domain.

You will handle end-to-end development—from identifying use cases to deploying AI features in production. You must have experience building real-world, production-grade AI and agentic systems, not just POCs.

Responsibilities

• Partner with product owners and finance experts to identify strong AI use cases in Accounts Receivable.
• Design and build predictive models, generative AI features, and multi-agent systems tailored to business problems.
• Develop LLM-based copilots and autonomous agents, including human-in-loop flows, security guardrails, and audit trails.
• Work closely with software engineers and data scientists to embed AI features into the product.
• Build and maintain secure, scalable MLOps pipelines for training, deployment, and monitoring.
• Continuously evaluate and improve model performance and user impact.
• Stay current with the latest advancements in LLMs, NLP, multi-agent frameworks, and applied AI engineering.
• Set up and tailor AI demos as needed for customers, stakeholders, and internal teams.
• Contribute to a culture of innovation, collaboration, and continuous learning.

Required Experience

AI/ML/LLM Experience

• 7+ years of AI/ML engineering experience.
• 3+ years of hands-on experience with LLM-based solutions.
• 1+ year of experience building agentic systems (production-ready, not POCs).

Multi-Agent & Autonomous Systems

• Strong understanding of multi-agent architectures, memory systems, tool-use, orchestration, routing, and safety guardrails.
• Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.

Technical Skills

• Strong programming skills in Python (preferred), R, or Java.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Solid understanding of predictive modeling, NLP, ML algorithms, and statistics.
• Experience working in cloud environments (AWS/Azure/GCP) with model deployment and data pipelines.
• Knowledge of GitHub/GitLab, version control, and CI/CD practices.
• Basic understanding of web fundamentals (HTTP, JSON, authentication) and REST APIs to integrate AI/LLM solutions into the product.

General Skills

• Strong analytical and problem-solving skills.
• Ability to communicate complex concepts clearly to non-technical partners.
• Great collaboration and teamwork abilities.
• Curiosity and passion for innovation in AI and Finance.

Tekion seeks an exceptionally talented and seasoned Staff / Lead Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.  
 
Key Responsibilities 

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges. 

• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions. 

• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives. 

• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services. 

• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation. 

• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth. 

• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership. 

• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI 

Core Competencies & Technical Expertise 

            The successful candidate will demonstrate mastery in the following areas: 

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI. 

• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data. 
   
   

Deep Learning: 

• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch. 

• Extensive experience implementing advanced neural network architectures. 

• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies. 

• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications. 

Technical Proficiencies: 

• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous. 

• Proficiency with cloud computing platforms (GCP, Azure, AWS). 

• Expertise in experimental design (A/B testing, causal inference). 

• Proficient in version control systems (Git). 

Required Qualifications 

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field. 

• A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value. 

• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach. 

• Proven experience in programming, data manipulation, and building models in a business context. 

• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences. 
   

Ideal Candidate Profile 
 

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving. 

• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable. 

• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred. 

• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences. 

• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams. 

• A commitment to continuous personal and team development within a collaborative, high-performance culture. 

Perks and Benefits

• Competitive compensation 

• Generous stock options 

• Medical Insurance coverage 

• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies 

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Agentic Systems & Next-Gen AI

• Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.

Cross-functional impact

• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.
• Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.

The experience we need

We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.

You should have experience with:

• Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, clustering, and time series.
• Experience in deploying ML workflows/models in production system
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
• Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Comfortable working in cross-functional teams.
• Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
• Excellent communication skills with the ability to simplify complex technical concepts.

Glance - An InMobi Group Company    

Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.   
 
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com

What should you know about joining Glance?  

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!

What You’ll Do

As a Data Scientist – Recommendation Systems, you will own and drive high-impact ML systems powering personalization across Glance products.

• Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources.
• Lead rapid experimentation—from hypothesis formulation to offline evaluation and online A/B testing—balancing speed, rigor, and business impact.
• Develop and productionize end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and monitoring.
• Partner closely with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions.
• Monitor model health and performance, applying statistical techniques to ensure robustness and long-term effectiveness.
• Explore and prototype new ML techniques to improve relevance, engagement, and monetization.
• Act as a technical interface for stakeholders, clearly articulating trade-offs, results, and next steps.
• Contribute to Glance’s thought leadership through blogs, case studies, and industry conference talks.

What We’re Looking For

Core Expectations

• Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale.
• Strong applied understanding of experimentation, metrics, and causal reasoning in real-world systems.
• Ability to take models from idea → prototype → production → business impact.

Experience & Skills

• 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems.
• Hands-on experience applying techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics.
• Strong programming skills in Python with production-quality code practices.
• Experience with big data ecosystems, especially Apache Spark.
• Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure.
• Experience operating in identity-constrained / privacy-aware environments (e.g., iOS/Android, identity-less systems) is a plus.
• Excellent communication skills—able to explain complex technical ideas clearly to non-technical stakeholders.
• High curiosity, strong problem-solving ability, and a bias toward learning and experimentation.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science.
• PhD is a plus, but not mandatory.
• We value diverse academic backgrounds—great data scientists come from many disciplines.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 8 - 10 years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 

• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 

• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency. 

• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

• Pragmatic: You automate the 80% and leave room for rapid experimentation. 

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
• Extensive experience implementing advanced neural network architectures.
• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
• Proficiency with cloud computing platforms (GCP, Azure, AWS).
• Expertise in experimental design (A/B testing, causal inference).
• Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

About Tekion

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform. Our Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Automotive Partner Cloud (APC) connect OEMs, retailers, and consumers through one seamless platform. Utilizing cutting-edge technology, big data, machine learning, and AI, Tekion is transforming the automotive retail ecosystem. We're inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it with offices in North America, Asia, and Europe, Tekion employs around 3,000 people worldwide.

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

The Role

We're looking for an AI-Native Product Manager to own one or more of our core agentic analytics product areas. This is not a traditional PM role where you write specs and hand them off. This is a role where you'll be deeply in the product, using AI tools daily, making autonomous calls, and shipping continuously.

You'll own the full lifecycle — from understanding why a pharma brand manager can't trust an AI insight, to defining the product, to shipping it, to measuring whether it actually changed a decision.

What You'll Own

You'll work across one or more of Tellius's core product pillars:

• Conversational Analytics — Natural language interaction with enterprise data. Users ask questions; AI agents investigate autonomously and deliver insights with reasoning and evidence. Handles both structured data warehouses and unstructured documents.
• AI-Generated Interfaces — Moving beyond static dashboards to dynamic, context-aware visualizations. The system generates the right interface for each specific insight — whether that's summary cards, interactive charts, or narrative explanations.
• Onboarding & Setup Automation — Reducing time-to-first-insight from days to minutes. AI-powered workflows that understand data relationships, suggest transformations, and validate configurations before users go live.
• Cross-Platform Intelligence — Bringing Tellius's AI capabilities into the tools users already work in. Ambient assistance that understands context across different enterprise applications.
• Vertical Intelligence — Pre-configured domain knowledge for specific industries (pharma, CPG, finance) — understanding their metrics, workflows, and decision-making frameworks out of the box.

You won't own all of these simultaneously. You'll own the ones that match your experience and where you can drive the most impact. But you'll need to understand how they all connect — because Tellius is a platform, and the product decisions in one area affect all the others.

What "AI-Native" Means Here

This isn't a role where "AI" is a buzzword in the job title. We mean it operationally:

You will use AI tools to do your job. Prototyping, research synthesis, competitive analysis, spec drafting, data exploration — all of it. If you're not reaching for an AI tool first, you're working the wrong way here.
You will build AI products. The products you ship involve autonomous agents making decisions, surfacing insights, and taking actions. You need to understand — at a working level — how LLMs reason, where they fail, how to design for uncertainty, and how to build trust into AI-driven workflows.
You will think in systems. Agentic analytics isn't a single feature. It's a web of interconnected capabilities: memory, semantic layers, reasoning chains, action workflows, and governance. Your job is to make these systems work together coherently for real enterprise users.

What We're Looking For

Must-Haves

1.  Deep AI Product Experience: You've shipped products where AI/ML is the core interaction, not a bolt-on. You understand the difference between "AI-powered" and "AI-native." You've wrestled with hallucination, confidence calibration, and explainability in production — not just in theory.
2.  AI Evaluation & Testing Expertise: You've built evaluation frameworks to test and validate agent behavior at scale. You understand how to use LLM-as-a-judge for automated testing, create human evaluation rubrics, design test scenarios that catch edge cases, and measure output quality beyond simple accuracy metrics. You know the difference between vibes-based testing and rigorous validation.
3.  Enterprise Analytics Domain Knowledge: You know what a pharma commercial analytics director actually does on a Tuesday. You understand semantic layers, data governance, metric definitions, and why an enterprise user needs to audit an AI's reasoning before acting on it. You don't need to write SQL, but you need to understand why the query matters.
4.  Agentic Systems Thinking: You can design product experiences where AI agents work autonomously — and where humans need to understand, guide, and override that autonomy. You think about agent memory, multi-step workflows, proactive vs. reactive triggers, and how to show reasoning without overwhelming users.
5. Speed and Autonomy Tellius is a 75-person company moving fast. You'll make calls without perfect information. You'll ship before it's polished. You'll iterate based on real user feedback, not months of research. You need to be comfortable with this pace and thrive in it.
6. Cross-Functional Collaboration You'll work closely with 44 engineers, 3 other PMs, designers, and a small GTM team. You need to be the person who connects engineering capability to business needs. Sales and CS are your frontline intelligence — you should be in their world regularly, not just at QBRs.

Strong Signals

• 5+ years of product management experience, with a majority in growth-focused roles
• You've built products in analytics, BI, data platforms, or AI/ML
• You've worked in a company serving regulated industries (pharma, finance, healthcare)
• You understand and can articulate the difference between a dashboard product and an agentic product
• You've designed for AI transparency and explainability
• You can prototype and use AI tools fluently in your workflow
• Technical background or ability to work effectively with engineering teams
• You ask, "What decision does this enable?" before "What feature should we build?"

What We Don't Need

• A PM who treats AI as a feature checkbox
• Someone who needs 6 months of onboarding before shipping anything
• A process-heavy PM who needs a fully defined roadmap before starting work
• Someone who can't navigate ambiguity — our product surface is expanding rapidly

What You'll Do (Day-to-Day)

Understand the user deeply. Talk to pharma commercial managers, CPG RevOps teams, and finance analysts. Understand their workflows, their trust requirements, and their relationship with data. Don't rely on secondhand intel — be in the room (or on the call).
Define and ship product. Write lightweight specs (not 20-page PRDs). Work with engineers to understand technical constraints and possibilities. Make trade-off calls. Ship. Measure. Iterate.
Use AI to move faster—prototype with AI tools. Synthesize research with AI. Draft specs with AI. Explore data with AI. If you're doing something manually that AI could do, stop and fix that first.
Think about the platform. Every feature you build connects to the broader Tellius platform. A decision about how Kaiya surfaces insights affects how Apps renders them, which affects how the Browser Extension presents them. Think in systems.
Drive outcomes, not features. Your success metric isn't "shipped 12 features this quarter." It's "influenced 50 enterprise decisions" or "reduced time-to-insight from 20 hours to 30 minutes." We measure value by what changes in the real world, not what ships in the product.
Own trust and governance. Enterprise users — especially those in the pharmaceutical and financial industries — need to trust AI outputs. You'll think about explainability, audit trails, data lineage, and confidence communication as core product requirements, not afterthoughts.
Culture: We're an AI-first, outcome-focused, and lean organization. We don't do unnecessary meetings. We do write things down. We move fast and iterate. We trust each other to make calls. And we care deeply about building products that enterprise users actually trust.

Compensation & Benefits

• Competitive base salary + equity (Series stage, early growth)
• Full benefits package

Learning budget for courses, conferences, and tools

Ready to Apply?

We don't want a cover letter. We want to see how you think.

Send us:

1. A product you've shipped that involved AI as a core interaction — what was the hardest trust or explainability problem you solved?
                                             OR
2. If you had 30 days at Tellius, what's the first thing you'd investigate and why?

That's it. Keep it short. We'll know if you're the right fit.

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

The Agents team at Google DeepMind India is driven by the mission of developing foundational capabilities in Large Models towards realizing AGI. We focus on uncovering emergent agentic behaviors through novel reinforcement learning algorithms run at scale.  

We also apply our research advances to Gemini and critical product launches in Google, touching the lives of hundreds of millions of users, and we are looking forward to doing more!

We are seeking a highly motivated and innovative Research Scientist to join our team in Bangalore, focused on advancing the state-of-the-art in autonomous agents  through reinforcement learning and ML optimization methods. You will conduct cutting-edge research on large language models (LLMs), focusing on the development of more capable, robust autonomous agents.

The Role

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence.

Having pioneered research in the world's leading academic and industrial labs in PhDs, post-docs or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They develop solutions to fundamental questions in machine learning and AI.

Key responsibilities:

• Design, implement and evaluate models, agents and software prototypes of large foundational models.
• Push the boundary of state of the art RL methods and machine learning optimization methods to build autonomous agents. 
• Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals.
• Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
• Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You

You are a passionate and talented researcher with a strong foundation and a proven ability to conduct impactful research in AI. You embrace change and thrive under ambiguity. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges. You are passionate about seeing your research translated into real-world products that improve the lives of users and are eager to work in an environment where research has a direct path to product impact.  You are eager to see your research contribute to real-world applications and are driven by a desire to create positive change through AI.

• PhD in Computer Science, Artificial Intelligence, or a related field.
• Strong publication record in top-tier machine learning conferences or journals.
• Solid understanding of deep learning, natural language processing, computer vision, and/or speech processing.
• Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.

In addition, the following would be an advantage: 

• Experience with multimodal learning, large language models, and/or assistive AI agents.
• Experience with prompt engineering, few-shot learning, post-training techniques, and evaluations.
• Familiarity with large-scale model training and deployment.
• Strong programming skills in Python or similar languages.
• Excellent communication and collaboration skills.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Role Purpose 

The Machine Learning Engineer III will play a critical role in advancing Jumio's Extraction team's mission to develop and enhance state-of-the-art solutions for data extraction for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market

Role Value 

As a Machine Learning Engineer III at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in machine learning, deep learning, and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally.

Example Responsibilities

. 

• Design and implement machine learning, deep learning, classical CV and NLP algorithms focused on data extraction.
• Research to support the deployment of advanced algorithms.
• Develop, evolve, and support production-quality code.
• Deploy models as AWS SageMaker endpoints or directly onto devices.
• Stay updated with the latest advancements in deep learning, computer vision, and NLP by engaging with academic papers and attending industry conferences.
• Work collaboratively with other engineers and product managers in an Agile development environment.

Experience and Qualifications 

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• A minimum of 6+ years of commercial experience in the field of computer vision, ML or a related area, not including time spent studying (5 years with Master’s).
• Proficiency in computer vision, deep learning and natural language processing techniques.
• Proficiency in working with LLMs and VLMs.
• Hands-on experience with PyTorch or TensorFlow, OpenCV, SKLearn, and in developing production-grade Python code.
• Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
• Experience in building, training, and deploying ML models to production environments.
• Strong communication and problem-solving skills.

Great to have Experience and Qualifications 

• PhD in Computer Science or related field with a specialization in computer vision, deep learning or NLP.
• Experience in developing algorithms for OCR, text extraction and text understanding.
• End to end experience (training, deploying, monitoring) with shipping VLM and LLM models in a production environment.
• Understanding of Spring / Java based system architectures.
• Experience with cloud environments - AWS / GCP.

Jumio Values 

• IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation

@Work
Our newest office, Jumio is in Prestige Tech Park III and growing fast. A hub of technical excellence with Machine Learning enablement at its core the engineers and team are committed to learning and innovation. They set the bar high. In a recent culture survey, these attributes were rated particularly highly in Jumio’s Indian offices.

What Will You Do?

Engineering Manager, Site Reliability(SRE) combines software and systems engineering to build and run large-scale, distributed, fault-tolerant systems.

We are looking for a passionate Engineering Manager, Site Reliability to join our team. As the founding member of the SRE team at Moveworks in Bengaluru, you will be responsible for architecting and managing Moveworks AI cloud infrastructure and strategy. As Moveworks grows fast, this team will be tasked with designing and operating resilient and secure cloud and infrastructure that allows our products to operate reliably and our engineering teams to build and release customer facing features very rapidly.

You will get to work closely with platform, infrastructure, machine learning, search, data, DevOps, and frontend teams, and build systems that allow these teams to ship high quality software at a rapid pace. This might include building/improving CI/CD pipelines, supporting blue/green deployments, creating/managing canary environments and ensuring that the likelihood of bad code getting into production is minimized.

• Improve observability and reliability of Moveworks systems by managing/building monitoring and alerting infrastructure.
• Improve debuggability -  build / manage systems that help debug issues in production and analyze performance.
• Architect, design, and execute projects to improve the reliability of our applications and systems.
• Be a technical lead for the adjacent teams in Bengaluru.

What You Bring To The Table?

• Bachelor’s degree in Computer Science or a related field.
• 8+ years of experience in software engineering / SRE with significant experience in Python / Go.
• 2+ years of experience leading projects and designing, analyzing, and troubleshooting distributed systems.
• Experience in managing/building infrastructure systems for deployment and management of workloads in AWS. Familiarity with Jenkins, Terraform, Ansible, Helm, etc. 
• Experience with Azure would be a plus.

What You Will Do:

• Design, build, and operate highly performant and scalable batch and stream data processing infrastructure and solutions to support day to day ML operations including training, serving, evaluation and experimental systems.
• Design and develop Moveworks’ foundational data models, data warehouse, real-time and offline processing pipelines using AWS EMR Spark, Apache Kafka, AWS Athena, Snowflake, Airflow, Apache HUDI, etc.
• Closely work with machine learning teams and data science teams to understand their data needs, influence data team’s roadmap, and lead as well as execute on various projects. 
• Build a data governance platform for secure and compliant data management, including services for data cataloging, lineage, audit, deletion and masking.
• Build and operate Orchestration platform that includes Temporal and Airflow, enabling other teams to develop features and workflows.
• Build out platform and data services/APIs to make data available to various different stakeholders and for customer facing data products

What you bring to the table:

• 5+ years of experience as senior/software engineer
• Experience with Python or Golang or Java or C++
• Experience with cloud infrastructure like AWS/GCP/Azure
• Experience with relational or non-relational databases such as Postgres, AWS DataLake/S3 or DynamoDB or Snowflake
• BS or higher in Computer Science or a related field.

What You Will Do?

• Build out core infrastructure services and microservices that impact our machine learning, frontend, and platform teams.
• Build out core infrastructure for various functionalities such as: distributed configuration management, rate limiting, feature flag, A/B testing, and traffic capture and replay.
• Improve the performance, scalability and observability of the Moveworks cloud infrastructure.
• Deliver deadline sensitive work regularly that is interdependent with other engineering teams.
• Own features end-to-end, and regularly influence the infrastructure roadmap.

What You Bring To The Table?

• 8+ years of experience designing, building, shipping, and maintaining backend distributed systems.
• Familiarity with Python/Golang/Java/C++.
• Experience with containers/Docker, and with cloud infrastructure like AWS/GCP/Azure.
• Desire to work at a startup pace with a high degree of ownership.
• Experience solving for performance, optimization, scalability, latency, and monitoring.
• Strong motivation, gumption, and an appetite for continuous, incremental changes and completing challenging projects quickly.
• BS in computer science or a related field.
• High level of curiosity about engineering outside of your immediate discipline and an incessant desire to learn.

The Solution Sales Manager will oversee market success of ServiceNow's Moveworks products. These products are built on our market leading Service Management platform and create a single source of truth that allows enterprise processes to execute with uniform information.

What you get to do in this role:

The Solution Sales Manager supports the strategy and solution win for specialty solution areas depending on engagement model. Responsibilities/ activities can vary by solution area given coverage capacity.

• • Support territory strategy and planning to improve vertical understanding, account use case targeting and execution
  • Provide input to AE during the account planning process based on territory strategy and recommendation
  • Ensure recommendation to territory strategy and account planning is aligned with Now Value principles
  • Support customers to envision the value of a digital transformation and support development of strategy by partnering with rest of account team, customer and partners.
  • Interlock with SC & Specialist SC on Capability Roadmap for feedback and agreement and team based on engagement model
  • Coach AEs, ADRs, ACE with foundational specialty solution area knowledge to identify specialty solution opportunities and help manage the sales cycle
  • Customize the time allocation of responsibilities to the needs of the territory and account team and celebrate successes
  • Champion diversity and belonging to contribute to an open and inclusive environment

What do you bring to the table?

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 5+ years knowledge on return on investment of specialty solutions area to lead solution win
• Experience as an AE, or in alternative sales/ customer service role
• Understanding of business sales processes
• Traver required: 30-50%

Compensation Structure: Base + Commission + Equity

Senior Product Designer II, India

Moveworks is an Enterprise SaaS company that solves complex problems using the latest ML & NLP technologies. Backed by industry leaders, Bain Capital & Lightspeed Ventures, and founded by well recognized serial entrepreneurs, Moveworks is transforming the ITSM market with autonomous resolution. Our product is well defined, our customers are already asking for more, and new demand is astounding. 

As a Senior Product Designer who will work closely to build a ‘best in class’ consumer interface for an enterprise SaaS product. In this role, you will be a voice for the user in all relevant product and business discussions. You will be responsible for ensuring we are shipping a product that solves user problems in the most elegant & simple way, incrementally and iteratively. You will be part of our early India Product Design team that helps to shape how our data products will evolve our operations and business decisions internally and externally. 

What  You Will Do:

• Define the user experience and visual language of a game changing product
• Develop design flows, including user journey and storyboards that incorporate information architecture, Web UI design & wireframes 
• Collaborate with product and engineering to bring your ideas to life while meeting scope and technical feasibility
• Effectively articulate design concepts and UX processes while building rapid prototypes for internal and external stakeholder alignment
• Elegantly and intuitively transform complex enterprise challenges into simple solutions 
• Conduct usability testing, user research & interviews and share findings with the entire team. Our view is that the best designers are a conduit of information which empowers the cross functional teams to make informed decisions.
• Analyze qualitative & quantitative data to develop approaches to meet product needs 

What You Bring To The Table :

• Bachelor’s  degree in UX design, engineering design or cognitive science/human factors or equivalent relevant experience
• 7 years+ of product/interaction design experience with enterprise UI/SaaS standards, as well as, Mobile standards
• Must have a portfolio of examples of interaction & visual design work
• Must have experience shipping Enterprise Admin experiences 
• Must have experience leading other designers as a project lead

Good To Have Skills: 

• Have people management and/or hiring experience 

• Have experience working with Machine Learning or Data Analytics / Visualization products in the past

What You Will Do:

As a Moveworks Product Analyst, you are an expert in deconstructing complex problems by utilizing your technical depth to identify creative solutions made available by integrating to a new platform. You have an understanding of APIs, authentication as well as familiarity common enterprise platform paradigms including concepts such as tickets, groups, approvals. You are able to build a deep understanding of all the ways a platform works - including the various ways a platform can be customized which can have implications to integration design decisions. You are someone who can bridge the technical with the enterprise and cultivate relationships with both internal and external stakeholders. You feel most at home when working hand in hand with data, engineering and customer success. 

• Build out the Moveworks 3rd party Integration strategy including playing a key role in investigating, planning and executing on new 3rd party Integrations such as ITSM, ERP, CRM, HRIS, IGA platforms. 
• Build out Stakeholder experience products to gain visibility and control of the Moveworks Platform 
• You will inspire & support engineering teams to achieve their goals through collaborative goal setting, project definition, milestone development, and tactical support throughout the project
• You will ensure our designers deeply understand customer pain and can test their ideas rapidly  
• You will support our deployment team in helping customers realize product value quickly

What You Bring To The Table:

• You have 3-6 years experience in a technical role
• You have 2+ years experience working with and building product leveraging other product APIs
• You have a proven track record of taking ownership of product goals and delivering against them
• You have sound framework for when to iterate, when to discard, and when to scale products
• You have technical and domain experience delivering scalable distributed software on the cloud
• You will win the trust of CIOs and IT Managers at F500 companies to enable rapid product deployment
• You will drive product development from concept to launch and successful iteration in a fast-paced customer obsessed organization
• You have the skills needed to take input from multiple sources, crystallize clear priorities, and communicate them effectively
• You have the ability to create product specs that identify problems, opportunity, goals, metrics, as well as, use cases and product requirements that help design and engineering teams develop solutions and measure success