Customs Associate Jobs

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, an

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Instawork’s on-demand labor marketplace is uniquely valuable for robotics and physical AI. We’re working with leading frontier labs to create the highest-quality, highest-diversity datasets for training robotics foundation models. Instawork Robotics is the human advantage in the robotics revolution. We are seeking a highly skilled, Field Engineering Technician to manage the maintenance, calibration, and local deployment of a fleet of 600 custom wearable camera rigs. Unlike standard IT support, this role sits at the intersection of precision electronics, mechanical assembly, and field operations. You will be the primary guardian of our hardware integrity, ensuring that high-stakes egocentric data collection continues without interruption across various deployment sites. About IRL Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . Who You Are: Field Engineering Technician – Wearable Devices Experience: 0–2 years Shift: Rotational Location: Bangalore Employment type: 1 year contract Role overview We are

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking Manufacturing Engineers to lead the development of processes, tooling, and prototype builds for custom motors and actuators. You will own a primary area as a Stator Process / Manufacturing Engineer, Tooling / Fixture Engineer, or Prototype Manufacturing Engineer, taking that work from early development through validation and repeatable execution in close partnership with mechanical, electromagnetic, electrical, test, quality, and supplier teams. These roles focus on the development, integration, and validation of electromechanical manufacturing capabilities, including stator winding processes, assembly and inspection tooling, and actuator prototype builds. You will help translate engineering designs into reliable hardware while establishing scalable processes, equipment, and build practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 5 days a week. In this role, you will Each opening focuses on one of the three specialties below, with shared responsibility for reliable processes and hardware. Stator Process / Manufacturing: develop and validate stacking, winding, termination, and potting processes. Establish process parameters, work instructions, and defect controls that produce consistent results across trained operators. Tooling / Fixture: design and deliver winding tools, assembly fixtures, inspection gauges, and bench equipment, from CAD and drawings through fabrication, commissioning, and troubleshooting. Improve setup time, labor, and repeatability. Prototype M

About PostHog We equip every developer to build successful products . We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including a built-in data warehouse , a customer data platform , and Max AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. Next on the roadmap are messaging, customer analytics, ai task creation and coding based on customer data, logs and support analytics. Our values are not a poster on the wall full of aspiration. They’ve come from how we really work, day in day out. PostHog is open source product led, and a default alive company that is well funded. Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient groups of cracked engineers who can outship much larger companies because they own their products end-to-end. Time for building: Nothing gets shipped in a meeting. We're a natively remote company. We default to async communication – PRs > Issues > Slack. Tuesdays and Thursdays are meeting-free days , and we prioritize heads down building time over perfect coordination. This will be the most productive job you've ev

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! As a Senior Salesforce Developer at New Relic, you will be responsible for building and maintaining our Salesforce org. You will work closely with our Sales Revenue & Finance teams to automate processes and build custom applications on the Salesforce platform. In this role, you will be responsible for the full development life cycle, from Design and Solution to deployment and maintenance. The ideal candidate will have 5+ years of experience as a Salesforce developer and be proficient in Apex, Lightning Web Components and Visualforce. They will also have experience with integrations and be able to work with other team members or independently. Duties & Responsibilities Design, develop, test, deploy, and maintain high-quality Salesforce.com solutions Configure Salesforce.com to meet business requirements Write Apex classes, triggers, Visualforce pages, and Lightning Web Components Integrate Salesforce.com with other systems (as needed) Perform data migrations Stay up to date on the latest Salesforce.com features Handle multiple projects simultaneously Work closely with business analysts, project managers, and other developers Adhere to coding standards and best practices Required Skills and Qualifications 5+ years of experience in Salesforce development, configuration, and customization Advanced Apex programming skills, including batch jobs, triggers, web services, and unit testing Experience with Lightning Components, Visualforce, and Force.com integration techno

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog makes products self-driving . It's the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Desktop , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change wh

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 The Billing Configuration team enables extensibility of all Billing concepts and owns the core infrastructure needed to manage configuration changes over time and custom billing logic use cases. What you'll do As the engineering manager for Billing Configuration, you’ll own the operational and technical direction of the platforms that let Stripe users and internal teams model, customize, and evolve how billing works. You’ll lead the team building the foundational configuration layer for Stripe Billing, enabling flexible products, pricing, eligibility, entitlements, and billing behavior. This team enables complex custom use cases and configuration changes over time. You’ll shape the team as it expands to support increasingly sophisticated use cases, working closely with internal and external customers to build reliable, extensible systems that make Stripe Billing adaptable to the real world. Responsibilities Lead a team responsible for the core architecture needed to enable billing configuration complexity and extensibility Own the technical strategy and roadmap for billing configuration Drive operational excellence across billing infrastructure systems Hire and develop engineers as the team expands into new scope Partner with stakeholders across organizations to deliver billing solutions Work backwards from internal and external customer needs to define priorities and scope Define and uphold engineering standards across a team owning busines

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 The Billing Configuration team enables extensibility of all Billing concepts and owns the core infrastructure needed to manage configuration changes over time and custom billing logic use cases. What you'll do As the engineering manager for Billing Configuration, you’ll own the operational and technical direction of the platforms that let Stripe users and internal teams model, customize, and evolve how billing works. You’ll lead the team building the foundational configuration layer for Stripe Billing, enabling flexible products, pricing, eligibility, entitlements, and billing behavior. This team enables complex custom use cases and configuration changes over time. You’ll shape the team as it expands to support increasingly sophisticated use cases, working closely with internal and external customers to build reliable, extensible systems that make Stripe Billing adaptable to the real world. Responsibilities Lead a team responsible for the core architecture needed to enable billing configuration complexity and extensibility Own the technical strategy and roadmap for billing configuration Drive operational excellence across billing infrastructure systems Hire and develop engineers as the team expands into new scope Partner with stakeholders across organizations to deliver billing solutions Work backwards from internal and external customer needs to define priorities and scope Define and uphold engineering standards across a team owning busines

Principal Solutions Engineer - UK Amplitude is where product teams go when they're serious about understanding their users. We're the leading product analytics platform, and our customers range from some of the most recognised brands in the world to fast-moving scale-ups. Our new product agent Wave closes the development lifecycle by connecting data insights into code and moving companies towards self improving products! In this role, you'll be the technical quarterback for our most strategic opportunities in the UK. You'll partner with Account Executives to win complex, multi-stakeholder deals by translating product capabilities into business outcomes that matter to Product, Marketing, and Analytics leaders. You'll lead technical discovery, architect custom proof-of-concept implementations, and serve as a trusted advisor to prospects navigating their digital analytics strategy. Your technical credibility and business acumen will directly influence the annual pipeline. What you’ll do… Deal Execution (70% of time) Lead technical evaluation phases for deals ranging from 100K to 1M+ ARR Conduct deep discovery to map prospect workflows, tech stack dependencies, and decision criteria to Amplitude's differentiation Design and execute hands-on proof-of-concepts that prove value within the prospect's actual data and use cases Handle technical objections related to data architecture, privacy/compliance, and integration complexity Present to C-level executives and translate technical capabilities into ROI narratives Internal Collaboration (20% of time) Partner with Software Engineering and Product Management to communicate feature gaps and customer requirements that affect deal velocity Act as a business partner to the Account Executives, advising and providing technical partnership throughout the sales cycle. Work with Customer Success to ensure smooth handoffs and technical alignment during implementation Mentor junior Solution Engineers on technical positioning and demo be

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 The Billing Configuration team enables extensibility of all Billing concepts and owns the core infrastructure needed to manage configuration changes over time and custom billing logic use cases. What you'll do As the engineering manager for Billing Configuration, you’ll own the operational and technical direction of the platforms that let Stripe users and internal teams model, customize, and evolve how billing works. You’ll lead the team building the foundational configuration layer for Stripe Billing, enabling flexible products, pricing, eligibility, entitlements, and billing behavior. This team enables complex custom use cases and configuration changes over time. You’ll shape the team as it expands to support increasingly sophisticated use cases, working closely with internal and external customers to build reliable, extensible systems that make Stripe Billing adaptable to the real world. Responsibilities Lead a team responsible for the core architecture needed to enable billing configuration complexity and extensibility Own the technical strategy and roadmap for billing configuration Drive operational excellence across billing infrastructure systems Hire and develop engineers as the team expands into new scope Partner with stakeholders across organizations to deliver billing solutions Work backwards from internal and external customer needs to define priorities and scope Define and uphold engineering standards across a team owning busines

About the Role Language Requirements: We prefer the hire to be Tri-Lingual with English, Spanish and Portuguese. English and Spanish are required. As a Senior Solutions Engineer at Amplitude, you'll be the technical quarterback for our most strategic opportunities in Northeast. You'll partner with Account Executives to win complex, multi-stakeholder deals by translating product capabilities into business outcomes that matter to Product, Marketing, and Analytics leaders. You'll lead technical discovery, architect custom proof-of-concept implementations, and serve as a trusted advisor to prospects navigating their digital analytics strategy. Your technical credibility and business acumen will directly influence the annual pipeline. What You'll Do Deal Execution (70% of time) Lead technical evaluation phases for deals ranging from 100K to 1M+ ARR Conduct deep discovery to map prospect workflows, tech stack dependencies, and decision criteria to Amplitude's differentiation Design and execute hands-on proof-of-concepts that prove value within the prospect's actual data and use cases Handle technical objections related to data architecture, privacy/compliance, and integration complexity Present to C-level executives and translate technical capabilities into ROI narratives Internal Collaboration (20% of time) Partner with Product Management to communicate feature gaps and customer requirements that affect deal velocity Work with Customer Success to ensure smooth handoffs and technical alignment during implementation Mentor junior SEs on technical positioning and demo best practices Thought Leadership (10% of time) Contribute to our competitive intelligence on tools like Google Analytics 4, Adobe Analytics, and Mixpanel Develop reusable demo assets, technical content, and proof-of-concept frameworks for the broader SE team What We're Looking For Required 5+ years in software pre-sales (SE, Sales Consulting, or technical Account Management roles) Language Requirements: Tri-L

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and