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Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

At Rockstar Games, we create world-class entertainment experiences. Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. Rockstar is looking for a Lead Software Engineer to join our Online Services team, who is passionate about games and will serve both as an individual contributor and as a leader for a skilled and diverse group of developers. This is a full-time, in-office position based in Rockstar’s large game development studio in Bangalore, India. WHAT WE DO The Rockstar Games Online Services Team is a development group, passionate about growing and maintaining the technology platform that powers Rockstar’s online titles and our ability to deliver outstanding player experiences. We build connected experiences that are found across our game franchises. We architect and maintain high-impact features to support the development of the Rockstar community and websites. We build services and tools that support our consumer-facing experiences and our internal business needs. RESPONSIBILITIES Lead a team of software engineers in maintaining and upgrading React and .NET systems. Define key results, set team objectives, provide technical expertise and mentorship. Conduct performance evaluations and regular check-ins to ensure team members are on track and aligned with goals. Develop and communicate technical roadmaps to leadership. Collaborate with Product Management and Production teams to scope and prioritize projects. Integrate systems with multi-functional teams. REQUIREMENTS 8+ years of professional software development experience at an enterprise level organization, with 3+ years of experience leading an engineering team of 4+. Efficiently facilitate communication with teams in various locations worldwide. Experience working in

SPECIFIC JOB RESPONSIBILITIES Defensive Operations (SecOps): Design and automate the Security Incident Response (SIR) and Vulnerability Response (VR) lifecycles. Build playbooks in Flow Designer to automate threat containment and remediation. Offensive Operations: Develop custom scoped applications to track penetration testing results, manage red-team engagement lifecycles, and automate the ingestion of reconnaissance data. Compliance & GRC: Configure and customize Integrated Risk Management (IRM) modules to map technical controls to frameworks like SOC2, ISO 27001, HIPAA, and FedRAMP. Integrations & Orchestration: Build robust, secure integrations (REST/SOAP, IntegrationHub , MID Servers) with our XDR, SIEM (Splunk/Sentinel), and cloud-native services (AWS/Azure/GCP). Multi-Tenancy & MSSP Architecture: Architect a scalable, multi-tenant environment that ensures strict data isolation between clients while allowing for unified " ClickOps " and Terraform-driven automation. AI & Innovation: Explore and implement Now Assist (GenAI) and AI-heavy workflows to automate security reporting and incident summarization. Defensive Operations (SecOps): Design and automate the Security Incident Response (SIR) and Vulnerability Response (VR) lifecycles. Build playbooks in Flow Designer to automate threat containment and remediation. Offensive Operations: Develop custom scoped applications to track penetration testing results, manage red-team engagement lifecycles, and automate the ingestion of reconnaissance data. Compliance & GRC: Configure and customize Integrated Risk Management (IRM) modules to map technical controls to frameworks like SOC2, ISO 27001, HIPAA, and FedRAMP. Integrations & Orchestration: Build robust, secure integrations (REST/SOAP, IntegrationHub , MID Servers) with our XDR, SIEM (Splunk/Sentinel), and cloud-native services (AWS/Azure/GCP)

You love turning real business problems into working AI solutions — and you’re not afraid to roll up your sleeves to ship them. In this role, you’ll lead Diligent’s internal AI Solutions function , a small, high-impact team that is embedding AI and GenA I into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering. You’ll set the AI vision and roadmap for internal tools, architect solutions, and still build hands-on — from prototypes and reference implementations through to production-grade integrations . You’ll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you’ll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business. If you enjoy being a “player-coach” who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales. Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives. Design and deliver end-to-end AI/GenAI solutions — from ideation and prototyping through production deployment, monitoring, and continuous improvement. Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way. &nbsp

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

About Prophecy The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how the world's top enterprises turn data chaos into reliable insights. We introduce the AI-native data lifecycle (generate, refine, deploy) where our industry leading AI agents and humans work hand-in-hand in visual and document interfaces to analyze, transform and prepare data, to ship trusted insights at enterprise scale. To learn more, visit us on LinkedIn. Position Summary This is an exceptional opportunity to be a technical leader on the team that powers the heart of Prophecy: the Runtime, our orchestration and execution service. Every data workflow , whether generated by our AI data agents or built by a human in the visual editor , is planned, scheduled, and run at enterprise scale by Runtime, directly against the customer's own platform (Databricks, Snowflake, BigQuery, and more). When a business user asks an agent a question and sees trusted results seconds later, Runtime is what made it happen. As a Staff Engineer, you will set the technical direction for this service: the distributed execution engine, the task coordinator, the multi-engine connectors, and the fast interactive previews that make the AI-native experience feel instant. You will own hard, ambiguous, high-leverage problems end-to-end , from architecture to production reliability , and raise the bar for the engineers around you. We're seeking A players to work with A players. We're a high-growth company on a once-in-a-lifetime journey to revolutionize the way data is prepared and analyzed. Be a part of it. The impact you will have Own the engine behind the product. Architect and evolve the runtime service that turns agent- and human-authored data workflows into high-performance jobs that run reliably in production and interactively during authoring. This is deep-tech at the center of the platform. Make it fast and make it scale. Design the distributed execution and task-coordination layer , schedul

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Lead DFT Engineer Job Description: Developing silicon for edge-to-cloud computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities: Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory /Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis . Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements: Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Bachelor’s degree in a related field. Tools:

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

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. Responsibilities Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization. Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges. Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations. Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR). Implement parsing, semantic analysis, and IR generation for deep learning frameworks. Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers. Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. Qual

About Sigmoid Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best-in-class end-to-end data value chain capabilities spanning Data Science, Data Engineering, and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team-first mindset. You'll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices: New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. Role: Associate Director - Delivery About the Role You will lead delivery for large-scale Data Engineering programs, working closely with clients to architect and drive execution of modern data platforms - data pipelines, cloud migrations, lakehouse implementations, and real-time data processing solutions. You will own end-to-end delivery governance across multiple engagements, act as a senior escalation point for clients, and provide technical and delivery leadership to teams building enterprise-grade data engineering solutions. If you enjoy operating at the intersection of technical depth in Data Engineering and delivery leadership, we would like to talk to you. Required Skills & Competencies 15-18 years of experience in Project Delivery, Client Engagement, or Data Engineering Delivery Management, with a significant portion focused on Data Engineering programs. Strong hands-on exposure to Data Engineering tools and technologies, including cloud data platforms Proven experience in Analytics/Consulting/IT Services, managing complex Data Engineering project execution, architecture reviews, and governance. Exposure to US/Global clients, with experience handling client escalations. Ability to manage multiple Data Engineering project teams and pods, mentor Delivery/Engineering Managers and technical leads, and drive engineering process improveme

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Financial Systems Engineer at Vanta, you will own the end-to-end health and evolution of the tech stack, data, and system integrations across our Procure to Pay and FP&A verticals, and be a technical lead for procurement, planning, and finance data systems. Vanta's Financial Systems function builds, maintains, and supports the tools that Vanta's Finance & Accounting operate on. The team builds scalable, integrated, and high value solutions that enable Finance, Accounting, and RevOps to move quickly without trading away accuracy or auditability. Vanta's Finance Systems team is early, and Procurement and FP&A have historically had little systems representation. That makes this a rare chance to own foundational decisions rather than inherit them. You will be helping implement our first CPM tool, re-architect Zip end-to-end, and help build the finance data layer in Snowflake that everything downstream will run on, with the autonomy to set the standards the team builds on as we scale. What you’ll do as a Senior Financial Systems Engineer at Vanta: Own the architecture, configuration, and operational health of Zip (P2P) including workflows, integrations, customizations, and agentic buildout Serve as the internal lead implementing Vanta's first CPM tool, working with an implementation partner, and owning the product post-launch Partner with Data/Analytics to design the Finance and Accounting data model in Snowflake, translating FP&A and Accounting requirements into data plans and SQL models Architect and maintain integrations between NetSuite and adjacent systems (Salesforce, Stripe, Anrok, Tesorio, Workato

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The Opportunity Flexport is investing heavily in the next generation of fulfillment—and we’re looking for a Staff Program Manager, Strategic Initiatives who wants to be at the center of that transformation. This is not a traditional program management role. You will be the architect and hands-on builder of tomorrow’s Flexport Fulfillment network: deploying automation, designing processes, building decision tools, and creating the operational standards that define how we scale. You will own initiatives from whiteboard to go-live—and you will own the business case and ROI that justifies every dollar we invest. That means getting into the weeds on automation system design (ASRS, robotics, goods-to-person), building the financial models to size the opportunity, driving implementation on the floor, and tracking realized returns post-launch. You are accountable for the full lifecycle. You’ll sit at the intersection of operations, product, engineering, and technology—working across all functions to identify gaps, design solutions, and bring them to life. We want someone who thrives in ambiguity, loves solving highly technical problems, and isn’t afraid to get hands-on—whe