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 Problem

The state of the art is not good enough. That is not a gap in execution. It is a research frontier.We are building ML systems across three unsolved problem areas.

Integrity: detecting fraud and anomalous behavior across heterogeneous, adversarially non-stationary signals.
Evaluation: measuring technical skill in a world where AI writes the code, and the old proxies no longer hold.
Chakra: an autonomous AI interviewer that conducts, adapts, and evaluates technical interviews end to end. 

Each of these problems is hard in a different way. None of them have clean existing solutions to fine-tune from. The person we are hiring will define what good looks like, not inherit it.

What you will do

• Design and ship production ML systems across integrity, evaluation, and autonomous interview domains.
• Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration.
• Build evaluation infrastructure and benchmarking pipelines that give real confidence in what ships.
• Define the architecture and production bar for new signal categories from scratch.
• 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 and hold up under pressure.
• 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.
• Python is your primary language and the full stack from data pipelines to model serving is comfortable territory.
• The bar you hold yourself to is higher than the one the market has set.

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.

About AQR Capital Management 

AQR is a global investment management firm that provides investment management services to pooled investment vehicles including hedge funds, mutual funds, European funds (i.e. UCITS) as well as to separately managed accounts (SMAs). AQR was established in August 1998 and has been engaged in trading equities, fixed income, currencies, commodities and derivatives across the globe. AQR employs long/short equity, arbitrage, global macro, alternative investments (i.e., absolute return and total return), and multi-style strategies, among others, to make its trades. AQR's clients include institutional investors, such as pension funds, insurance companies, endowments, foundations, and sovereign wealth funds, as well as financial advisors and high net worth individuals. AQR’s clients can choose to invest through various AQR fund complexes and structures (i.e. Master-Feeder structures, RICs, UCITS etc.) or through separately managed accounts. AQR currently manages close to 200 legal entities for the various fund structures.

The AQR Tax Team is a globally integrated function with professionals located across the U.S., U.K., the Philippines, and India. The team plays a critical role in managing the firm’s global tax compliance, reporting, and advisory responsibilities, supporting a wide range of investment vehicles and legal entities. The India tax team forms an important part of this global footprint, contributing to tax compliance, fund reporting, investor reporting, and process efficiency initiatives. In addition to core compliance responsibilities, the team partners closely with colleagues across Finance, Legal, Operations, Business Development and Investment teams to ensure alignment on regulatory requirements, support new product and entity launches, and assess the tax implications of evolving business strategies. The AQR Tax Team ultimately reports to the Head of Tax and then to the Chief Financial Officer (CFO), and functions as part of the broader Finance department.

With the support of fund administrators and Big 4 accounting firms, the AQR Tax department manages the tax compliance function for its investment entities. Fund administrators prepare detailed tax workpapers, while Big 4 firms prepare tax forms, execute filings, and provide advisory support on complex tax and regulatory matters.

Job description: This role is responsible for tax compliance, reporting, and oversight for hedge funds and mutual funds.

Your Role

• Review taxable income calculations and related tax adjustments such as wash sales, straddles, constructive sales, and other book-to-tax differences
• Review hedge fund tax allocations, including tax transfers, and fill-up/fill-down special allocations
• Review Schedules K-1/K-3 along with the required statements and footnotes
• Review mutual fund-specific items such as year-end distributions, shareholder reporting, annual gross income tests, and asset diversification tests
• Review federal and state tax returns and related forms, including Form 1065, Form 1120-RIC, Form 8613, and Form 8621
• Review international tax filings such as Form 1042/1042-S, FBAR, Form 8865, Form 5471, and PFIC statements
• Manage relationships with external tax vendors to ensure compliance with annual tax delivery calendars and timely submission of deliverables
• Prepare reconciliation schedules and supporting workpapers to facilitate tax reviews
• Address investor tax inquiries by providing reconciliations and well-documented responses
• Develop scenario analyses and models in response to ad-hoc requests from internal and external stakeholders
• Collaborate with fund treasury, legal, operations, and other internal teams to resolve tax reporting and compliance matters
• Review annual tax estimate workpapers for hedge funds and mutual funds
• Maintain and update review procedures to capture current tax developments and changes
• Navigate and analyze tax data to deliver accurate reporting solutions for internal and external stakeholders

What You’ll Bring

• Knowledge of U.S. taxation of hedge funds
• Knowledge of U.S. taxation of mutual funds is a plus
• In-depth understanding of financial instruments and their U.S. taxation
• Must be highly organized, with excellent multi-tasking skills and ability to prioritize activities effectively.
• Must be comfortable making decisions on product design and analysis.
• High attention to details
• Excellent command of the English language - oral and written
• Strong analytical, technical and research skills
• Can work with minimal supervision and deliver high quality output.
• Must be proactive, motivated and team player
• Proficient in MS Office applications, particularly MS Excel
• AI tools and knowledge of AI in context to automation of US tax work

Education and Experience:

• Bachelor’s degree in accounting
• CPA or EA will be an added advantage
• 2+ years of tax experience within the asset management industry
• Experience with U.S. partnership and corporate taxation
• Experience with U.S. taxation of hedge funds
• Experience with U.S. taxation of mutual funds is an advantage

Who You Are

• Mature, thoughtful, and a natural fit for a collaborative, team-oriented culture
• Hard-working and eager to learn in a fast-paced, innovative environment
• Committed to intellectual integrity, transparency, and openness
• Motivated by the transformational effects of technology-at-scale

• 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

 Please complete the attached Internal Transfer Request Form and submit.   

Please make sure to apply with your Coupang e-mail address.   

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

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

Job Duties and Responsibilities

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

Required Skills:

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

Education and Certifications

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

#P25153_3431422
#Linkedin_Hybrid

Company Overview

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

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

What You’ll Be Doing

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

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

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

What we are looking for -

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

Why you will love to work with us -

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

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

Overview

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

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

What You’ll Do

As a Director of Engineering at Five9, you will:

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

What You Bring

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

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

Why Join Us

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

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there.

Our culture is modelled around expertise and mutual respect with a team first mindset. Youʼll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.

Offices: New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office.

About the Role:

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

Role: Gen AI Presales Leader

Key Responsibilities:

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

Desired Experience & Education:

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

Who we are

About Stripe

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

About the team

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

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

What you’ll do

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

Responsibilities

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

Who you are

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

Minimum requirements

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

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

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

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

What Makes This Role Unique 

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

What You’ll Do 

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

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

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

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

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

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

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

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

What We’re Looking For 

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

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

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

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

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

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

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

• Experience taking models from prototype to production 

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

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

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

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

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

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

The team works on building highly scalable, secure, reliable, enterprise grade SaaS contact center software applications with a Build, Test, Deploy, Maintain, Own mindset, using Microservices based architecture and AWS services. Talkdesk solution supports millions of real time interactions on a scalable data platform across Voice and Digital Channels, offers several NLP and AI capabilities and provides actionable insights to administrators, agents and supervisors. Talkdesk AppConnect offers unparalleled integrations with industry leading apps. This position would be based in Bengaluru, will report to an Engineering leader, and would play a key role to design and implement highly reliable and feature rich services with end to end ownership of the services.

Responsibilities:

• Design, implement, test and maintain SaaS services and features hosted on AWS, ensuring they are completed on time, and meet quality and five 9’s reliability standards.
• Work in a modern agile software engineering environment (with source code control, dev/stage/prod release cycle, extensive automated testing, and continuous deployment).
• Manage your work through the use of Github, Jira, and Talkdesk systems.
• Have end to end ownership of microservices, adhere to safe deployment practices, and operate with a DevOps mindset.
• Implement microservices with Security, Reliability, Telemetry as first principles, avoid technical debt.
• Implement automated unit, API and functional tests in a CI/CD environment.
• Work closely with cross-functional teams, including Product Management, Principal Engineers, SRE, Platform to ensure that all aspects of design and implementation are aligned.
• Actively participate in backlog grooming, design and code reviews.
• Identify and prioritize technical debt.
• Own reliability for your services and participate in on-call rotation. Resolve production incidents 24x7. Apply learnings from RCAs.
• Conduct research and stay up-to-date with industry trends and emerging technologies, making recommendations for their adoption as appropriate.
• Ensure that all engineering work is completed in compliance with industry regulations and standards.

Qualifications:

• Bachelor's or Master’s degree in Computer Science or a related field.
• 2-5 year of experience architecting and implementing highly-available, reliable, secure SaaS applications based on microservices architecture.
• Expertise in Microservices, AWS, Java, Python, JavaScript, React, Spring Boot, Data streaming technologies, APIs, Messaging queues, Caches, CI/CD, Telemetry.
• Expertise with cloud telephony, UCaaS, CCaaS, SIP, SBC, integration with CPaaS providers.
• Experience with one or more database technologies (ex: PostgreSQL, MySQL, MongoDB).
• Experience with Docker/Kubernetes container technologies.
• Experience with REST API design and implementation.
• Experience with streaming technologies such as Kafka, Flink.
• Experience with modern automated testing, CI/CD pipelines and SaaS tools.
• Passion for producing clean, standards-compliant, secure code.
• Proficient with automated unit and API testing, continuous integration and safe deployment practices.
• Fearless about learning new technologies and technical approaches to application development.
• Experience working in a geographically distributed team.
• Excellent written and verbal communication skills.

This is an onsite role based at Nextiva’s Bengaluru office (Wilshire III by MFAR, 492, Hobli, RHB Colony, Mahadevapura, Bengaluru, Karnataka 560048). Working together onsite strengthens how we operate, enabling faster decisions, clearer communication, and stronger execution, so you can make a greater impact and move work forward with speed and clarity. 

In-Office Expectation: This role is expected to work onsite five days per week, supporting a highly collaborative, in-person team environment. 

We're looking for a strategic, hands-on Principal Product Manager to lead the vision and execution for our next-generation Voice capabilities within our CX platform. You'll build and evolve cutting-edge, AI-powered voice experiences—transforming traditional voice interactions into intelligent, automated conversations that enhance agent productivity, customer satisfaction, and operational efficiency through advanced NLP, real-time transcription, and voice AI. You'll shape the vision, align cross-functional teams, and deliver a roadmap that drives measurable business impact.

Key Responsibilities:

1. Strategic Ownership

• Define the long-term product strategy and positioning for Voice capabilities (UCaaS and CCaaS), aligned with AI-first differentiation and competitive market value
• Deeply understand user needs across contact center operations, IT leaders, developers, and end-users; incorporate voice-of-customer and competitive insights in every decision
• Partner with Finance and Sales to inform packaging, pricing, and monetization decisions for voice features (stand-alone vs. bundled) using data-driven insights

2. Execution & Delivery

• Translate strategy into a data-informed roadmap; prioritize features such as:
  • AI-Powered Transcription: Real-time speech-to-text with speaker diarization, punctuation, vertical specific grammars and multi-language support
  • Natural Language Processing (NLP): Intent detection, sentiment analysis, entity extraction, and conversation voice understanding
  • Voice AI & Automation: Conversational IVR/IVA, AI agents for self-service, voice bots with LLM integration
  • Real-Time Voice Analytics: Call monitoring, keyword tracking, compliance detection, and live agent assistance
  • Voice Infrastructure: SIP trunking, call routing, voice quality optimization, codec support, and telecom carrier integrations
  • UCaaS/CCaaS Features: Click-to-call, voicemail-to-text, call recording, conference bridging, call transfer, and omnichannel voice integration
• Collaborate closely with Engineering, Design, Data Science, and GTM teams to deliver high-impact releases; establish clear metrics that link customer outcomes to business goals
• Drive continuous iteration post-launch through telemetry, experimentation, A/B testing, and customer feedback

3. Cross-Functional Impact

• Act as a connector across Product, Design, Data Science, Engineering, and GTM to ensure cohesive delivery and alignment on vision
• Champion a culture of experimentation, learning, and accountability across teams
• Influence senior stakeholders through crisp storytelling and data-backed recommendations; translate technical voice capabilities into compelling business value

4. Technical & Domain Expertise

• Demonstrate deep understanding of:
  • Voice Technologies: VoIP protocols (SIP, RTP, WebRTC), telephony systems, PBX/softswitch architectures, audio codecs
  • AI/ML for Voice: NLP, ASR (Automatic Speech Recognition), TTS (Text-to-Speech), LLMs, RAG (Retrieval Augmented Generation)
  • Transcription & Speech Analytics: Real-time transcription engines, speaker identification, acoustic modeling, language models
  • Contact Center Voice: ACD (Automatic Call Distribution), IVR/IVA systems, call routing strategies, CTI (Computer Telephony Integration)
  • UCaaS Platforms: Unified communications features, presence, soft phones, mobile/desktop clients, and hardware devices.
• Stay current on competitive landscape (NICE, RingCentral, Dialpad, Five9, Genesys, Twilio) and emerging voice AI technologies
• Work with ISVs, technology partners, and telecom carriers to expand voice capabilities and ecosystem integrations

Qualifications:

Required Experience & Skills

• 8+ years in SaaS Product Management, including 4+ years leading enterprise-grade contact center, UCaaS, or voice communication products
• Proven success transforming embedded voice capabilities into revenue-generating, standalone experiences that drive customer adoption and satisfaction
• Deep technical expertise in:
  • Voice communication protocols; telephony device and systems
  • NLP, speech recognition, and conversational Voice technologies
  • Contact center voice infrastructure (IVR, ACD, call routing)
  • Real-time transcription and voice analytics
• Track record of developing and executing successful product launches in competitive voice/CCaaS markets with a CX-first approach
• Strong analytical, problem-solving, and decision-making skills with data-driven approach to prioritization
• Experience managing beta programs, user feedback loops, and conducting A/B testing for voice features
• Excellent collaboration skills with ability to motivate product development teams, work effectively across functions, and lead through influence in global environments

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field; MBA or similar advanced degree is a plus
• Experience with AI concepts including NLU (Natural Language Understanding), ML model training, LLM integration, and RAG architectures
• Familiarity with voice analytics, compliance requirements (PCI-DSS, HIPAA for voice), and quality standards
• Understanding of Centrex features, hosted PBX, SIP trunking, and carrier integrations
• Prior experience as a software engineer, technical lead, or solutions architect before transitioning to product management
• Knowledge of developer platforms and APIs for voice (Twilio, Vonage, RingCentral APIs)

Personal Attributes

• Proven affinity for inserting user experience first in the product design approach, especially for voice interactions
• Ability to demonstrate deep understanding of the Conversational AI (Voice/Chatbot) landscape, LLM technology, ecosystem, and evolution
• Embrace a hands-on approach, capable of navigating from high-level strategic vision to detailed execution
• Become the reference for competitive intelligence on voice offerings in the market
• Champion for voice product throughout each product's lifecycle, from strategic definition to technical design to market launch

What Success Looks Like in 12 Months

• Vision & Roadmap: A clear two-year vision and KPI-driven roadmap influencing cross-product alignment
• Customer Impact: Delivery of new AI-assisted QM/WFM capabilities adopted by at least three flagship customers with >70% engagement
• Commercial Influence: Measurable attach rates and incremental ARR growth in key regions (North America, EU, APAC)
• Operational Excellence: Instrumentation provides real-time insights into adoption, feature performance, and churn drivers
• Cross-Functional Collaboration: Strong partnerships across Product, Engineering, and GTM driving faster iteration and impact

Why Join Us

• Lead the transformation of voice communications through cutting-edge AI technology
• Work with a talented, cross-functional team passionate about building world-class CX solutions
• Shape the future of how millions of agents and customers interact through voice
• High visibility role with direct impact on company strategy and revenue
• Competitive compensation, equity, and benefits package

Nextiva DNA (Core Competencies)

Nextiva’s most successful team members share common traits and behaviors:

• Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success.
• Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking, and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies.
• Right Attitude: They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams.

Total Rewards

Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office.

Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses.

• Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity.
• Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means.
  • Coverage Type - Employee Only
  • Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000
  • Free Cover Limit - 1.5 Crore
• Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays
• Financial Security💰 - Provident Fund & Gratuity
• Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives
• Growth 🌱 - Access to ongoing learning and development opportunities and career advancement

At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! 

Beware of Recruitment Fraud: At Nextiva, we follow a merit-based hiring process and do not charge any fees or require a deposit at any stage.  We also do not authorize any third parties to collect payments or sensitive information on our behalf. 

All genuine communications from Nextiva originate from official email addresses ending in “@nextiva.com”.  Communications received from free email services (such as Gmail, Yahoo, or Hotmail) purporting to be from Nextiva should be treated as fraudulent.  If you are contacted by a third-party claiming to represent us, please verify their credentials by writing to [talent@nextiva.com]. 

We encourage candidates to stay vigilant and verify the authenticity of any communication claiming to be from Nextiva, including unsolicited calls, WhatsApp messages and Telegram communications. While we strive to maintain a secure hiring process, Nextiva is not responsible for any losses arising from fraudulent activities.

For genuine opportunities, please apply only through our official careers site: [Careers URL / Nextiva LinkedIn authentic jobs].

If you believe that you have been a victim of recruitment fraud, please contact your law enforcement agencies immediately.

#LI-AK1 #LI-Onsite

At Talkdesk, we are courageous innovators focused on redefining the customer experience, making the impossible possible for companies globally. We champion an inclusive and diverse culture representative of the communities in which we live and serve. And, we give back to our community by volunteering our time, supporting non-profits, and minimizing our global footprint. Each day, thousands of employees, customers, and partners all over the world trust Talkdesk to deliver a better way to great experiences.

We are recognized as a cloud contact center leader by many of the most influential research organizations, including Gartner and Forrester. With $498 million in total funding, a valuation of more than $10 Billion, and a ranking of #8 on the Forbes Cloud 100 list, now is the time to be part of the Talkdesk legacy to help accelerate our success in a new decade of transformational growth.

At Talkdesk, we embrace FAST, our fundamental operating principles that define who we are as an organization. These principles drive us to make the impossible possible. FAST: Focus + Accountability + Speed = Talkdesker.

• Focus: Focus time, energy and attention on what is most impactful for the business and thoughtful about how and when to partner with others.
• Accountability: Hold self and others accountable to meet commitments and drive results. Accept responsibility for successes and failures.
• Speed: Execute with agility and urgency. Act promptly, decisively, and without delay. Make good and timely decisions that keep the organization moving forward.
• Talkdesker: YOU!

The team builds highly scalable, secure, and reliable enterprise-grade SaaS contact center applications with an AI-first mindset, leveraging microservices architecture and AWS. Development follows a Build, Test, Deploy, Maintain, Own model, enhanced by AI-assisted workflows, copilots, and agent-based delivery approaches.

The Talkdesk platform powers millions of real-time interactions across voice and digital channels on a scalable data platform, enriched with NLP and AI capabilities to enable intelligent routing, automation, and actionable insights. The team actively leverages custom agent development and AI copilots to automate workflows, accelerate development, and improve operational efficiency. Talkdesk AppConnect enables seamless integrations with leading enterprise applications.

This Bengaluru-based IC role reports to an engineering leader and requires hands-on ownership in designing, building, and operating highly reliable, feature-rich services end-to-end, with a strong focus on leveraging AI tools, agent-based systems, and copilots to drive productivity and innovation.

Duties and Responsibilities:

• Design, implement, test, and maintain SaaS services and features hosted on AWS, ensuring timely delivery, high quality, and five 9’s reliability standards, leveraging AI tools and copilots on a daily basis to accelerate development and improve code quality.
• Maintain a growth mindset by continuously adopting emerging technologies and proactively automating repetitive processes.
• Work in a modern agile software engineering environment, actively using AI-assisted workflows (e.g., copilots, code generation, test generation) across the dev/stage/prod lifecycle, with strong automated testing and continuous deployment practices.
• Manage your work through the use of Github, Jira, and internal systems, incorporating AI tools for task automation, code insights, and productivity improvements.
• Have end-to-end ownership of microservices, applying agent-based delivery models and AI-assisted development practices, while adhering to safe deployment and DevOps principles.
• Implement microservices with Security, Reliability, and Telemetry as first principles, leveraging AI-driven insights to proactively identify risks and avoid technical debt.
• Implement automated unit, API, and functional tests in a CI/CD environment, utilizing AI tools for test case generation, coverage improvement, and validation.
• Work closely with cross-functional teams (Product, Principal Engineers, SRE, Platform), using AI-assisted analysis and collaboration tools to align on design and implementation.
• Actively participate in backlog grooming, design discussions, and code reviews, leveraging AI for code analysis, review assistance, and design validation.
• Identify and prioritize technical debt, using AI tools to surface inefficiencies, suggest refactoring opportunities, and improve maintainability.
• Own reliability for your services and participate in on-call rotation; use AI-assisted observability and incident analysis tools for faster triage and resolution of production issues, applying learnings from RCAs.
• Continuously research and adopt emerging AI tools, agent frameworks, and engineering practices, integrating them into daily workflows to improve team productivity.
• Ensure all engineering work complies with industry regulations and standards, leveraging AI where appropriate for compliance checks and documentation.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 2–5 years of experience designing and building highly available, scalable, and secure SaaS applications using microservices architecture.
• Hands-on experience with AI development tools (e.g., GitHub Copilot, Claude) with a strong inclination to use them daily; familiarity with agent-based delivery models and the ability to build and automate workflows using custom AI agents.
• Strong expertise in backend and distributed systems technologies, including microservices, AWS, Java/Kotlin/Python/JavaScript, Spring Boot, APIs, messaging systems, caching, CI/CD, and observability/telemetry.
• Experience with real-time and streaming systems (e.g., Kafka, Flink) and designing scalable data pipelines.
• Experience with cloud telephony and communications platforms (e.g., UCaaS, CCaaS), including protocols such as SIP and integrations with CPaaS providers.
• Proficiency with one or more database technologies (e.g., PostgreSQL, MySQL, MongoDB).
• Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes).
• Strong experience in REST API design, development, and best practices.
• Experience with modern testing practices, including automated unit, integration, and API testing within CI/CD pipelines.
• Commitment to writing clean, secure, maintainable, and standards-compliant code, leveraging AI tools to improve quality and productivity.
• Comfortable adopting new technologies, AI tools, and engineering practices, with a continuous learning mindset.
• Experience working in geographically distributed teams with strong collaboration skills.
• Excellent written and verbal communication skills.

About Us

Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.

Each AI agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work.

Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.

Why Join Us

At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers. 

If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy. 

Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries.

What you’ll be doing

• Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment.
• Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI.
• Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform.
• Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.
• Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders.
• Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.
• Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform.
• Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc.

What you’ll bring to the role

• Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU.
• An engineering mindset with the competencies of an applied scientist. 
• 3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems.
• Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications.
• Good understanding of recent advances in building LLM-powered applications,  and multi-agent systems at scale. 
• Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production.
• Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development
• Excellent communication, collaboration skills, and presentation skills.
• Experience with Spoken Language Understanding is a plus
• Published papers in top NLP/ NLU conferences or workshops are a plus
• Relevant open-source contributions are a plus.

Perks & Benefits

• Excellent medical insurance options and free online doctor consultations
• Yearly privilege and sick leaves as per Karnataka S&E Act
• Generous holidays (National and Festive) recognition and parental leave policies
• Learning & Development fund to support your continuous learning journey and professional development
• Fun events to build culture across the organization
• Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.)

Our Commitment to Inclusion and Belonging

Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.

We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.

If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.

About the Role

We are looking for a high-potential Product Manager Apprentice to join our Product Management team working on next-generation Contact Center as a Service (CCaaS) platforms. This role is designed for early-career professionals who are passionate about building enterprise SaaS products and want hands-on exposure to AI-driven customer experience technologies and modern cloud-native architectures.

As a Product Manager Apprentice, you will work closely with  Product Managers, Engineering, UX, Data Science, and GTM teams to define, build, and scale features across our CCaaS product lines — including AI-powered voice, digital, analytics, automation, workforce management and integrations platforms.

This is a learning-intensive role that provides real ownership, structured mentorship, and exposure to the full product lifecycle in a fast-growing SaaS environment.

Key Responsibilities

Product Discovery & Strategy Support

• Assist in researching customer problems across contact center domains such as Inbound, outbound campaigns, agent experience, AI automation, analytics, Quality Management, Workforce Management, and integrations.
• Analyze market trends in CCaaS, AI in CX, cloud communications, and SaaS platforms.
• Support product managers in defining product vision, value propositions, and roadmap priorities.

 AI & Data-Driven Product Development

• Work with AI/ML teams on features involving speech-to-text, NLP, LLMs, conversation intelligence, automation, and predictive analytics.
• Help translate AI capabilities into real-world customer use cases and measurable business outcomes.
• Contribute to defining product requirements for AI-enabled workflows and decisioning systems.

Requirements & Delivery Execution

• Assist in creating Product Requirement Documents (PRDs), user stories, and acceptance criteria.
• Work closely with engineering teams using Agile/Scrum methodologies to support sprint planning, backlog grooming, and release execution.
• Participate in feature demos, UAT coordination, and release readiness activities.

Modern SaaS Platform Exposure

• Gain hands-on experience with cloud-native, multi-tenant SaaS architectures, APIs, microservices, security, and scalability concepts.
• Support integration initiatives across CRM platforms (e.g., Salesforce), CPaaS providers, and enterprise ecosystems.

Customer & Stakeholder Engagement

• Join customer calls, usability sessions, and beta programs to capture feedback and validate product direction.
• Support preparation of product documentation, internal enablement, and launch materials.

What You Will Learn

• How enterprise CCaaS platforms are built and scaled.
• How AI is productized — from model capability to customer value.
• How to balance customer needs, technology constraints, and business strategy.
• How modern SaaS companies execute product management at scale.

Eligibility & Qualifications

• Bachelor’s degree in Engineering or Computer Science (or related technical discipline).
• Strong interest in Product Management, SaaS platforms, AI technologies, and cloud computing.
• Basic understanding of software development concepts, APIs, and web technologies.
• Familiarity with Agile development practices is a plus.

Desired Skills & Attributes

• Strong analytical and problem-solving mindset.
• Excellent communication and structured thinking skills.
• Curiosity about AI, data platforms, and digital customer experience technologies.
• Ability to work cross-functionally with engineering, design, and business teams.
• Entrepreneurial mindset with a bias for action and learning.

Career Path
This apprenticeship is designed to develop future Associate Product Owners , Associate Product Managers and Product Managers. High performers will have the opportunity to transition into a full-time product management role with increased ownership of product areas.

Why Join Us

• Work on a market-leading CCaaS platform from Five9 shaping the future of customer experience.
• Get early exposure to AI-first product development in a real enterprise environment.
• Structured mentorship from experienced product leaders.
• Opportunity to grow rapidly in one of the fastest-growing technology domains.

Job Title: AI Full stack developer

 About Us

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

WHY JOIN CAPCO? 

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

MAKE AN IMPACT

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

#BEYOURSELFATWORK

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

CAREER ADVANCEMENT

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

DIVERSITY & INCLUSION

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

Job Description:

P-926

The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 

As our Search product continues to evolve, we are seeking multiple  ML Engineers from junior levels to more senior levels to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

• Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. 
• Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. 
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. 
• Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

• BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
• 5+ years experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance
• Experience in one or more of the following:  
• Query understanding
• NLP
• Text mining
• Recommendations
• Personalization
• Discovery
• Conversational AI 
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects. 

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

Agentic Engineering Team

Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.

Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves.

Five9 has led the cloud revolution in contact centers, helping organisations transition from legacy premise-based solutions to the cloud. The cloud contact center market has become the hot space for innovation in real-time communications, and is the tip of the spear for the application of Artificial Intelligence, especially Generative AI and Large Language Models (LLM). Five9 has established itself as a leader in this market and has recently launched its AI Agents, providing the next-generation of self-service and customer experience.

Five9 is establishing an Agentic Engineering team in Bangalore, India. This team will sit on the bleeding edge of AI technology, and be responsible for the development of AI Agents on top of the Five9 platform. The team will own the entire lifecycle of AI Agent development, from requirements to development to testing to deployment to ongoing maintenance and improvement. Members of the team will utilize skills in prompt engineering, prompt design, agent and multi-agent architectures, function calling, and tool definition to build best-of-breed AI agents for real-world use cases. Prior experience in AI Agent development is highly desirable but not required.

Key Responsibilities:

• responsible for the development and testing of AI Agents for B2B customer experience use cases in healthcare, financial services, retail and beyond, which will become part of the product and available to Five9 customers globally to use with their customers

• Maintain expertise – through ongoing review of academic papers and competitive analysis of vendors – in the latest-and-greatest algorithms, techniques, and architectures for AI Agent design, and apply those to build best-in-class AI Agents

• Interface with customers and customer facing teams to understand requirements and use cases for which the AI Agent needs to satisfy

• Partner with the engineering team building the AI Agent platform, providing feedback on improvements that improve agent performance and reduce time to implement

Requirements:

• 3+ years of experience in development of conversational AI applications for customer service space, such as for healthcare, financial services or retail organizations

• 5+ years experience in customer-facing technical roles, such as professional services, customer support, technical account management, solutions consulting, technical sales, and so on

• Experience with commercial products used for the development of customer support and customer experience (CX) applications, such as Google Dialogflow, IBM Watson, Kore.ai, Five9, Genesys, NICE, Amelia, Omelia, and so on

• Expertise in conversational AI technologies, including speech recognition, speech synthesis, natural language processing, and large language models. Experience in creating such models is not required, only experience in using them

• Experience with AI Agent technologies, including prompt engineering, MCP, A2A, ReACT, LangChain, LangGraph, CrewAI, AutoGPT, Open Agents, Semantic Kernel, RAG, fine-tuning, and embeddings, is highly desired but not required

• Strong communication skills, including written and verbal communication in English

• Experience in hiring and building teams from scratch, including the usage of contractors

•  Bachelor’s or Master’s degree in Computer Science or equivalent work experience

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 The Role 

As a Research Engineer on the Inference ML team at Cerebras Systems, you will adapt today's most advanced language and vision models to run efficiently on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize models, gaining end-to-end exposure to cutting-edge inference research on the world's fastest AI accelerator. 

You will focus on pushing the frontier of speculative decoding, large-model pruning and compression, sparse attention, and sparsity-driven techniques to deliver low-latency, high-throughput inference at scale. 

Responsibilities 

• Implement and adapt transformer-based models (NLP and/or vision) to run on Cerebras hardware
• Assist in optimizing models for inference performance (latency, throughput)
• Run experiments, analyze results, and support model improvements
• Help bring up and validate models on the Cerebras system
• Debug and troubleshoot model or system issues with guidance from senior team members
• Support profiling and performance analysis using internal tools
• Collaborate with cross-functional teams (ML, software, hardware) on model integration

Minimum Qualifications 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 1–3 years of experience in software engineering or machine learning in a similar capacity (internships count)
• Experience with Python and at least one ML framework (e.g., PyTorch, Transformers, vLLM or SGLang)
• Understanding of deep learning concepts (e.g., neural networks, transformers)
• Experience with Generative AI and Machine Learning systems
• Strong programming skills in Python and/or C++

Preferred Qualifications 

• Experience with speculative decoding, neural network pruning and compression, sparse attention, quantization, sparsity, post-training techniques, and inference-focused evaluations. 
• Exposure to large language models or computer vision models
• Experience running experiments or tuning models
• Familiarity with tools like PyTorch, Hugging Face Transformers, or similar
• Basic understanding of performance concepts (e.g., latency, throughput)
• Experience working in Linux environments

About Five9

Five9 is a leading provider of cloud software for the enterprise contact center market, bringing the power of the cloud to thousands of customers and facilitating more than three billion customer interactions annually. Five9 has led the cloud revolution in contact centers, helping organizations transition from legacy premise-based solutions to the cloud. The cloud contact center market has become the hot space for innovation in real-time communications and is the tip of the spear for the application of Artificial Intelligence. Five9 has led the charge with its Genius AI platform. Five9 offers a high-energy environment with lots of room for personal and professional growth. Our innovative AI team is seeking a talented and experienced Senior Full Stack Software Engineer. In this role, you will be part of the team that builds software that brings AI technologies to users. Prior AI experience is not required - you will have the opportunity to integrate with AI technologies from vendors like Azure, OpenAI, Google, Databricks, IBM, and Amazon, and thus receive on-the-job experience for some of the hottest skills on the market. An ideal candidate for us is an experienced engineer who is passionate about building high performance web platforms and applications, a brilliant problem solver and a creative self-starter.

Role Overview

As a Senior Software Engineer, you will be part of the team that builds software that brings AI technologies to users. You will work on building high performance web platforms and applications, contributing to scalable and highly available systems, and collaborating with cross-functional teams in an agile environment while owning your code in production.

Key Responsibilities

• Implement UX designs by working with UX Designers on a day-to-day basis, using React/Redux based framework.
• Be part of an agile team to develop a scalable, highly available application platform using modern PaaS platforms such as GCP.
• Participate and contribute to requirements analysis and grooming.
• Understand how to leverage PaaS components, such as CDN, noSQL databases when developing software in order to achieve scalability, reliability, and operability.
• Ability to build custom widgets for dashboards developed using Google Looker Studio plugins is a plus, but not required.
• Document and communicate clearly architecture and implementation solutions.
• Have ownership of your code in production, including on-call, troubleshooting.

Qualifications & Skills

• 5+ years software development experience.
• React/Redux focus.
• Highly proficient in JavaScript and Java.
• Experience with PaaS hosted relational and no-SQL databases.
• Desirable, but not required, experience with custom widget development using Google Looker Studio.
• Experience in operational code ownership – on-call, troubleshooting, uptime.
• Experience in applying modern UI design patterns and separating concerns in a distributed system.
• Must have experience working within an Agile/Scrum team.
• Positive, self-motivated and enthusiastic attitude with a strong sense of ownership.
• Strong pro-active communication skills, both verbal and written.
• AI skills in speech recognition and natural language processing are a plus but not required.
• Experience in contact center software is a plus but not required.

Senior Software Engineer in AI - Java Spring, backend

Five9 is a leading provider of cloud software for the enterprise contact center market, bringing the power of the cloud to thousands of customers and facilitating more than three billion customer interactions annually. Five9 has led the cloud revolution in contact centers, helping organizations transition from legacy premise-based solutions to the cloud. The cloud contact center market has become the hot space for innovation in real-time communications and is the tip of the spear for the application of Artificial Intelligence. Five9 has led the charge with its Genius AI platform. Five9 offers a high-energy environment with lots of room for personal and professional growth. Our innovative AI team is seeking a talented and experienced Senior Full Stack Software Engineer. In this role, you will be part of the team that builds software that brings AI technologies to users. Prior AI experience is not required - you will have the opportunity to integrate with AI technologies from vendors like Azure, OpenAI, Google, Databricks, IBM, and Amazon, and thus receive on-the-job experience for some of the hottest skills on the market. An ideal candidate for us is an experienced engineer who is passionate about building high performance web platforms and applications, a brilliant problem solver and a creative self-starter.

Key Responsibilities:

• Be part of an agile team developing a scalable, highly available application platform using modern PaaS platforms such as GCP.
• Utilizing Java Spring Framework, Spring Boot and reactive programming pattern for creation of highly scalable, robust microservices.
• Participate and contribute to requirements analysis and feature grooming.
• Understand how to leverage PaaS components, such as message buses, cloud functions (lambdas), and noSQL databases when developing software in order to achieve scalability, reliability, and operability.
• End-to-end feature development from UI implementation all the way through the middleware and backend platform.
• Document and communicate clearly architecture and implementation solutions.
• Have ownership of your code in production, including on-call, troubleshooting.

Key Skills:

• 5+ years software development experience.
• Highly proficient in Java – Spring Framework, Spring Boot, reactive programming (desirably, but not required to have experience with rxjava or similar) and JavaScript.
• Experience with PaaS hosted relational and no-SQL databases (mySQL, BigQuery, DataStore, etc)
• Familiarity with vibe coding using different AI tools like Claud Code,
• Experience in developing automated test cases with modern tools such as Junit.
• Experience in operational code ownership – on-call, troubleshooting, uptime.
• Experience in applying design patterns and separating concerns in a distributed system.
• Experience with Web Technologies (HTML, CSS, DOM, JavaScript) and web standards (HTML5)
• Familiarity with client-side JavaScript Toolkits such as React is a plus but not required.
• Must have experience working within an Agile/Scrum team.
• Positive, self-motivated and enthusiastic attitude with a strong sense of ownership.
• Strong proactive communication skills, both verbal and written.
• Design and manage data pipelines to process AI-generated insights, ensuring reliable data flow, quality, and actionable outputs for decision-making.
• AI skills in speech recognition and natural language processing are a plus but not required.
• Experience in contact center software is a plus but not required.

P-1408

The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 

As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

• Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. 
• Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. 
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. 
• Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

• BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
• 10+ years experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance
• Experience in one or more of the following:  
• Query understanding
• NLP
• Text mining
• Recommendations
• Personalization
• Discovery
• Conversational AI 
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects. 

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

P-1407

The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 

As our Search product continues to evolve, we are seeking multiple ML Engineers from junior levels to more senior levels to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

• Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. 
• Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. 
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. 
• Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

• BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
• 6+ years experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance
• Experience in one or more of the following:  
• Query understanding
• NLP
• Text mining
• Recommendations
• Personalization
• Discovery
• Conversational AI 
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects. 

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

P-1407

The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 

As our Search product continues to evolve, we are seeking multiple ML Engineers from junior levels to more senior levels to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

• Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. 
• Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. 
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. 
• Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

• BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
• 6+ years experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance
• Experience in one or more of the following:  
• Query understanding
• NLP
• Text mining
• Recommendations
• Personalization
• Discovery
• Conversational AI 
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects. 

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

P-1408

The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 

As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.

Key Responsibilities

• Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. 
• Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. 
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. 
• Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For

• BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
• 10+ years experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance
• Experience in one or more of the following:  
• Query understanding
• NLP
• Text mining
• Recommendations
• Personalization
• Discovery
• Conversational AI 
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects. 

Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

What we want to accomplish and why we need you

Suki is a leading technology company that provides AI voice solutions for healthcare. Its mission is to reimagine the healthcare technology stack, making it invisible and assistive to lift the administrative burden from clinicians. Its flagship product is Suki Assistant, an AI assistant that uses generative AI to automatically create clinical documentation by ambiently listening to patient-clinician conversations. Suki helps clinicians complete notes 72% faster on average, assists with other tasks including coding and answering questions, and generates incremental revenue for organizations, delivering a 9X ROI in year 1. Suki also offers its proprietary AI and speech platform, Suki Platform, to partners who want to create best-in-class ambient and voice experiences for their solutions. Clinicians that use Suki already spend over 70% less time on administrative tasks, and we’re striving to do even better. Come and join us! 

We are a user-driven company and are committed to making sure every pixel of our product is in service of the doctors. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine. We’re confident enough to move fast and talented enough not to break things.

What will you do everyday?

The Machine Learning team forms the core of Suki's product, driving innovation and predictive excellence. You'll leverage your NLP expertise to enhance our computational infrastructure and improve our technical approaches  and algorithms. Working directly on the platform powering our domain services, you'll collaborate with cross-functional teams to address NLP challenges and scale our platform for thousands of doctors. You'll manage and curate large datasets, ensuring data quality and relevance for training and evaluation. You'll monitor and analyze system performance metrics, identifying areas for optimization and implementing necessary improvements. By staying updated on NLP and Generative AI advancements, you'll incorporate innovations to maintain our competitive edge, reducing doctors’ administrative burdens and significantly impacting their daily lives.

Ok, you're sold, but what are we looking for in the perfect candidate?

• Expertise: You know how to train models.  You understand which models work best, and use LLMs only when necessary. You watch out for recall, accuracy, and precision. In other words, you’ve done this before.
• Action oriented: You love to build. You like to ship fast, quickly iterate, and see amazement in users’ eyes.
• Creativity: You enjoy listening to user feedback and then building products in novel ways. You’re resourceful and enjoy finding alternate paths to success.
• Problem solving: you use data to help point you in the correct direction. You optimize relentlessly, and understand the impact you’re making on the business.
• Humility: You’re humble and love working in a team without ego to deliver products
• Adaptability: You thrive in a fast-moving organization that uses light-weight processes and cutting-edge technology to have a huge impact.
• Confidence: You trust your abilities and you’re ready to push yourself to the next level.
• Communication: You are a clear communicator and demonstrated consensus-builder.

Requirements

• 5+ years in overall Machine Learning experience, with at least three years focused on NLP and Contextual Embeddings.
• Proven record of an end to end workflow and with moving at least one NLP model to an enterprise production system.
• Expert in the understanding, practice, and deployment of state-of-the-art deep neural network models.
• Experience in building and maintaining distributed backend services for ML/AI Applications
• Strong grasp of CS fundamentals including abstractions, algorithms, probability, data structures and system design is preferred
• Strong working knowledge of LLMs, including prompting, orchestration, RAG, context and cost management
• Hands-on experience designing and implementing evaluation frameworks for LLM-based systems, including automated evals, human feedback loops, regression testing, and benchmark design

*We don’t necessarily expect to find a candidate that has done everything listed, but you should be able to make a credible case that you’ve done most of it and are ready for the challenge of adding new skills to your resume.

Tell me more about Suki

• On a roll: Named by Fast Company as one of the most innovative companies, named Google’s Partner of the Year for AI/ML, named by Forbes as one of the top 50 companies in AI .
• Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems.
• Great investors: We’re backed by Venrock, First Round Capital, Flare Capital, March Capital, Hedosophia and others. With our $165M raised so far, we have the resources to scale.
• Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it.
• Great customers: Our solutions are used in health systems and clinics across the country, supporting clinicians across dozens of specialties.  Check out what one of our users says about how Suki has helped his practice.
• Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better. 

Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.

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. 

About the Role:

Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity.

Requirements:
      Must have 

• 6+ years of experience as a software engineer, primarily with Python
• Ideally, you possess an advanced degree (Bachelor's / Master's)  in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered
• 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs). 
• Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering.
• Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing.
• Experience with LLM tracing, debugging and evaluation platforms such as Langfuse.
• Excellent communication, organizational, problem-solving, debugging, and analytical skills.

        Great to have 

• Experience in async processing of data at scale
• Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI.
• Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing.
• Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
• Previous experience in data extraction from specific domains (e.g., financial reports, news).
  
  

Responsibilities:

• Deploy LLM based production grade solutions.
• Fine-tune and adapt State of the art LLMs for specialized data extraction tasks. Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents.
• Solve Engineering challenges that come along with LLM solutions, such as high latency, non-deterministic output, etc.
• Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency.
• Integrate and manage LLM Observability to trace, debug, and monitor every extraction
• Own systems end-to-end, including(but not limited to) designing, coding, monitoring, testing, CI/CD and on-call support.

About the Role:

Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity.

Requirements:
      Must have 

• 6+ years of experience as a software engineer, primarily with Python
• Ideally, you possess an advanced degree (Bachelor's / Master's)  in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered
• 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs). 
• Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering.
• Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing.
• Experience with LLM tracing, debugging and evaluation platforms such as Langfuse.
• Excellent communication, organizational, problem-solving, debugging, and analytical skills.

        Great to have 

• Experience in async processing of data at scale
• Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI.
• Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing.
• Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
• Previous experience in data extraction from specific domains (e.g., financial reports, news).
  
  

Responsibilities:

• Deploy LLM based production grade solutions.
• Fine-tune and adapt State of the art LLMs for specialized data extraction tasks. Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents.
• Solve Engineering challenges that come along with LLM solutions, such as high latency, non-deterministic output, etc.
• Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency.
• Integrate and manage LLM Observability to trace, debug, and monitor every extraction
• Own systems end-to-end, including(but not limited to) designing, coding, monitoring, testing, CI/CD and on-call support.

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 

Technical Expertise:

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.

Applied Problem-Solving:

• Mandatory skill - Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.
• Mandatory skill - Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration:

• (Preferred) Proven ability to lead and mentor a junior applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Education & Experience:

• 3+ years of hands-on experience in applied machine learning and data science with Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field or appropriate experience.
• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 7+ years of hands-on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 5+ years of hands-on experience in applied machine learning and data science.

What you will do:

The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various aspects of hardware-software co-design. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.

What you will bring:

Minimum:
MS or PhD in Computer Engineering, Math, Physics, or related degree with 10+ years of industry experience Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals Proficient in C/C++ and Python development in Linux environment and using standard development tools Experience implementing algorithms in high-level languages such as C/C++ and Python Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, AI accelerators using libraries such as CuDA etc. Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc. Experience with development for embedded SIMD vector processors such as Tensilica. Self-motivated team player with a strong sense of ownership and leadership

Preferred:
Prior startup, small team, or incubation experience.
Experience with ML frameworks such as TensorFlow and/or PyTorch.
Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.
Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation.
Work experience at a cloud provider or AI comp.

Location: Hybrid, working onsite at our Bengaluru, India offices 3-5 days per week.

What you will do:

 The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development,

enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong

understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the

underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various

aspects of hardware-software co-design. You can build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the

compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.

What you will bring: 

Minimum:

MS in computer engineering, math, physics, or a related degree with 5+ years of industry experience or PhD in computer engineering, math, physics, or a related degree with 1+ years of industry experience

Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
Proficient in C/C++ and Python development in Linux environments and using standard development tools.
Experience implementing algorithms in high-level languages such as C/C++ and Python.
Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CUDA, etc. 
Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc.

Experience with development for embedded SIMD vector processors such as Tensilica.
Self-motivated team player with a strong sense of ownership and leadership.

Preferred:

Prior startup, small team, or incubation experience.

Experience with ML frameworks such as TensorFlow and/orPyTorch.

Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.

Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation

Work experience at a cloud provider or AI compute/subsystem company.

About the Role

We're looking for an AI Engineer to join the proAgent pod and work on the systems that power our autonomous voice agents in live financial conversations. You'll work alongside a small, high-agency team where you will have real ownership over features and components from day one.

This is a hands-on engineering role. You'll be deep in the code — building agent logic, integrating speech models, tuning prompts, and debugging gnarly real-time issues. You don't need to have done all of this before, but you need to be the kind of engineer who figures things out fast, takes feedback well, and ships.

What You'll Do

Agent Loop & Reasoning

• Build and maintain components of the agentic runtime that powers multi-turn financial conversations — covering payment negotiations, compliance guardrails, and objection handling
• Implement context management logic that tracks consumer state, conversation history, and business rules across long, branching dialogues
• Write and iterate on primitives that balance conversational fluidity with structured reasoning — the agent needs to feel human while making verifiable decisions

Voice AI Systems

• Work on our real-time voice pipeline with a target of sub-1s latency across transcription, reasoning, and synthesis
• Contribute to VAD tuning and turn-taking logic that makes conversations feel natural
• Help evaluate and integrate speech models (STT, TTS, speech-to-speech) — we currently work with ElevenLabs and Cartesia for TTS, and Deepgram for STT, and are always exploring what's next
• Debug streaming audio and WebRTC issues in production

LLM Infrastructure

• Write and refine prompts, implement orchestration flows, and contribute to model routing logic
• Build components of our evaluation framework — helping measure agent quality across conversation quality, empathy, and compliance adherence
• Stay curious about new models and tools — flag opportunities and contribute to build-vs-integrate discussions

What You Bring

• 2 – 5 years of hands-on engineering experience, with good exposure to building or working with ML or AI systems in production.
• Solid Python fundamentals — you are comfortable writing clean, maintainable code and debugging production issues.
• Some experience working with LLMs: prompt engineering, API integrations, or building simple pipelines or agents.
• High bias for action — you don't wait to be told exactly what to do, and you push yourself to ship rather than over-engineer.
• Strong fundamentals in Python; familiarity with TypeScript is a plus.
• Eager to learn in a fast-moving environment, take ownership of your work, and ask good questions.

Even Better

• Exposure to voice AI: speech recognition, synthesis, or telephony systems — even if only through personal projects or coursework
• Any background or interest in fintech, lending, or collections
• You've tinkered with Twilio, LiveKit, ElevenLabs, or similar real-time infrastructure
• You've built a small agentic system — even a side project — that combines LLM reasoning with structured actions
• Familiarity with streaming protocols, WebRTC, or low-latency system design

Why This Role

• Real ownership from day one: proAgent is a small pod. You won't be a cog — you'll own components, ship features, and see your work in live consumer conversations within weeks.
• Frontier work: voice AI that reasons, decides, and acts is one of the hardest problems in applied AI. You'll be learning by doing on problems most engineers never touch.
• Strong mentorship: you'll work directly with senior engineers and the AI Lead who will invest in your growth — this is a place to level up fast.
• High leverage early career: the decisions you make and the code you write will impact millions of financial conversations. Rare for an early-career role.

About the Role

We're looking for an AI Lead to own the technical direction and team behind proAgent's core intelligence. You'll lead a small, high-agency pod building AI Agents that handle nuanced financial conversations — where every millisecond of latency, every reasoning decision, and every team member's growth matters.

This is a player-coach role with full pod accountability. You'll write code, define the AI architecture, set the technical bar, and directly manage and grow a team of AI engineers. The right person has been in the weeds of voice AI and LLM systems long enough to have strong opinions — and has led teams long enough to know how to bring others along.

What You'll Own

Pod Leadership & Team Building

• Lead and grow the proAgent AI pod — hiring, mentoring, and developing a team of AI engineers who own everything from agent reasoning to voice pipeline optimization.
• Set the technical bar for AI engineering at Prodigal: what rigorous experimentation looks like, what production-readiness means, and how the team should make build-vs-integrate decisions.
• Run sprint cycles, technical reviews, and roadmap planning — keep the pod shipping fast without losing architectural coherence.
• Work directly with the CTO and product leadership to translate company priorities into a pod-level AI roadmap with clear milestones and ownership.

Agent Loop & Reasoning

• Own the architectural direction of the agentic runtime that powers natural, multi-turn conversations while executing complex business logic — payment negotiations, compliance guardrails, objection handling.
• Set the design standards for primitives that balance conversational fluidity with structured reasoning: the agent needs to feel human while making verifiable decisions.
• Define how the pod builds context management systems that track consumer state, conversation history, and business rules across long, branching dialogues.
• Drive the evolution of agent reasoning as model capabilities and product requirements grow — stay ahead of what's possible and what the business needs.

Voice AI Systems

• Own the technical strategy for our real-time voice pipeline — sub-1s latency across transcription, reasoning, and synthesis is a hard requirement, not a goal.
• Set the direction for VAD tuning, turn-taking logic, and the standards that make conversations feel natural at scale.
• Lead evaluation and integration decisions for speech models (STT, TTS, speech-to-speech) as the landscape evolves — we currently work with ElevenLabs and Cartesia for TTS, and Deepgram for STT, and are always exploring what's next.
• Establish engineering practices for debugging and optimizing streaming audio and WebRTC across the pod.

LLM Infrastructure

• Own Prodigal's prompting, orchestration, and model routing strategy — set the standards for the pod.
• Lead the design of evaluation frameworks that measure agent quality beyond accuracy: conversation quality, empathy, compliance adherence, and business outcomes.
• Stay current on model capabilities and make pragmatic build-vs-integrate decisions that balance shipping speed with long-term architectural health.
• Institute red-teaming, adversarial testing, and behavioral evaluation practices before changes reach production.

What You Bring

• 7+ years building production grade engieering systems, with 2+ years leading an AI engineering team or pod with direct reports.
• Proven track record of owning AI product outcomes end-to-end — from problem definition and architecture through production and iteration.
• Hands-on experience with LLMs in production: prompt engineering, orchestration, evaluation, and fine-tuning.
• High bias for action — real-time systems get gnarly fast, and you have a track record of pushing things to production rather than perfecting in isolation
• Strong fundamentals in Python and TypeScript.
• Demonstrated ability to hire and grow strong AI engineers — you know what great looks like and can develop people toward it.
• Clear technical communication — you can explain complex tradeoffs and system behavior to engineers, product managers, and client stakeholders alike.

Even Better

• Deep experience with voice AI: speech recognition, synthesis, telephony systems, and the real-time constraints that come with them.
• Background in fintech, lending, or collections.
• Hands-on experience with Twilio, LiveKit, ElevenLabs, or similar real-time infrastructure.
• You've designed and shipped agentic systems that combine LLM reasoning with structured actions at production scale.
• Track record of building and scaling small, high-performing AI teams from the ground up.
• Experience in instituting evaluation, observability, and red-teaming practices across a team — not just for your own work.

Why This Role

• High leverage: proAgent is poised to handle millions of live consumer conversations every day. Your architectural decisions and the team you build directly determine business outcomes.
• Frontier work: voice AI that reasons, decides, and acts is one of the hardest problems in applied AI — add compliance, empathy, and financial stakes, and it gets harder. We're building it.
• Real ownership: small pod, big scope, full accountability. You will shape what proAgent's intelligence becomes, and the team that builds it.
• Executive partnership: You will work directly with the CTO and the founding leadership. The decisions you make in this role will define Prodigal's AI strategy for years.

We're seeking a Machine Learning Lead to join our team in building cutting-edge products that shape the future of consumer finance. As a member of our team, you will oversee complex technical problems, build new features, and improve existing products. Our teams are constantly pushing the boundaries of applied intelligence in consumer finance, and we're looking for passionate individuals who can help us advance us further. If you're interested in leading a world-class team of engineers and researchers to work on exciting projects that have a significant impact, we encourage you to apply.

Responsibilities:

• Partner with the CTO to drive the team's goals and technical direction to pursue opportunities that make the organization more efficient
• Effectively communicate complex features and systems in detail
• Understand industry & company-wide trends to help assess & develop new technologies
• Partner with the CTO to lead long-term technical vision and roadmap for Machine Learning and the entire organization
• Suggest, collect, and synthesize requirements and create an effective feature roadmap
• Design and develop Machine learning products and services leveraging AI (LLMs, Agentic AI, classical ML, the modern NLP stack, etc)
• Architect and implement data pipelines for ML model training. Lead scalable software systems development to deploy ML models into production systems, ensuring high performance and reliability.
• Stay updated on ML research and the ever-changing Gen AI landscape, identifying opportunities for innovation.
•  Effectively collaborate with cross-functional teams to deliver high-quality solutions on time. Guide team members in contributing to ML design discussions for new projects.

Requirements:

• Extensive experience, 5+ years in software development, with a focus on machine learning and data science in a tech company. 
• Proven track record of delivering high-quality ML products in a fast-paced, agile environment.
• Deep understanding of machine learning algorithms with hands-on experience in developing and deploying machine learning models at scale.
• Strong coding skills in Python. Familiarity with machine learning libraries such as PyTorch and sci-kit-learn. Experience with data manipulation and analysis tools like Pandas and Spark.
• Strong communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and mentor junior engineers.

Preferred Qualifications:

• Experience with cloud services (AWS), Databricks, and building scalable, distributed systems.

Job Benefits 

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

Meet Sangram - (Cofounder and CTO) and hear his vision for Prodigal below (01:38)

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

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

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

What you’ll do:

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

What we’re looking for: 

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

Bonus Points:

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

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

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

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

What you’ll do:

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

What we’re looking for: 

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

Bonus Points:

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

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

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

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

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Implement large scale, low latency microservices, including discovering and solving complex issues at scale.
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• Help troubleshoot, analyze and root cause issues in the platform.
• You will work on microservices built with Golang, Scala, Java and Ruby, hosted in AWS.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  3-5 years of  work experience.
• Professional programming experience with Golang, Python, Scala, Java and/or Ruby+Rails.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Experience with implementing secure, scalable API services
• Experience with transactional databases and data modeling (Postgres, MySQL, DynamoDB or equivalent)
• Cloud development experience (especially AWS).
• A pragmatic and curious problem-solver. You thrive on breaking down complex challenges, asking insightful questions to understand the "why," and delivering effective, practical solutions.
• A high-ownership collaborator with keen attention to detail. You take full accountability for your work, communicate clearly with your team, and are obsessed with shipping high-quality, well-crafted code.

Bonus Points:

• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).
• Experience with functional programming in TypeLevel Scala (cats-effect, ZIO, FS2, etc).
• Experience with ML/LLMs (prompt engineering, RAG, classification, NLP, fine tuning etc) is a huge plus.
• Experience with AI development tools like Cursor, Claude Code, Github Copilot, etc.