Lead Python Specialist Jobs

About the job Shape how Graphcore’s high-performance systems are tested, diagnosed and proven ready for production. You’ll lead the technical direction for system-level manufacturing test. You’ll turn product requirements into robust test strategies for manufacturing partners. Your work will directly influence product quality across boards, blades and rack-level systems. You’ll solve complex test issues and drive improvements across products. You’ll define, deploy and maintain test platforms, fixtures and diagnostic solutions. You’ll also partner with hardware, software and manufacturing teams. This role combines hands-on technical depth with broad influence. You’ll shape future test strategy while helping other engineers raise the bar. The team and culture The Product Test and Diagnosis team finds and manages hardware defects across chips, boards and finished systems. Its work spans manufacturing sites and deployed products. You’ll work closely with engineering teams and manufacturing partners to solve problems quickly. Decisions are driven by evidence, technical judgement and root cause analysis. You’ll have ownership of complex problems and the scope to challenge existing approaches. You’ll also mentor engineers and establish practical standards across teams. What we’re looking for Essential Proven experience in PCBA and system product validation, including in manufacturing testing within production environments. Strong understanding of electronics fundamentals, PCBA/blade/rack-level manufacturing processes, and associated failure mechanisms. Proficient with Linux command-line environments and technical troubleshooting. Experienced in the local and remote operation of test equipment, including oscilloscopes, DMMs, clock generators, SMUs, and PSUs. Proven problem-solving, communication, and presentation skills, with the ability to perform effectively in fast-paced, complex environments. Desirable Strong knowledge of high-speed interconnects, including PCIe Gen5/6

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: As the Data Center Operations Manager, you’ll oversee the data center technicians who keep SpaceXSI's AI infrastructure running smoothly. This role is pivotal in ensuring our systems operate at peak efficiency, supporting the compute power behind our mission. You’ll co-lead a skilled team, manage critical operations, and implement smart, sustainable solutions. We’re looking for someone with technical expertise and a proactive approach to maintain and scale our facilities effectively. RESPONSIBILITIES: Oversee Site Operations: Manage power, cooling, networking, and hardware deployments to ensure 99.999% uptime for SpaceXSI's AI compute systems, keeping our infrastructure reliable and ready for innovation. Guide Your Team: Lead and develop a team of Data Center Operations Technicians through training, performance evaluations, and fostering a collaborative, high-performing environment tied to SpaceXSI's objectives. Streamline Processes: Take charge of hardware lifecycles, incident resolution, and inventory management, refining procedures to ensure your team operates with precision and consistency. Connect Key Players: Coordinate between technicians, SpaceXSI'

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h

About the Job: We're looking for an Engineering Manager for our Experimentation team. In this role, you'll lead the team that builds and operates the core Experimentation product, from setup to results processing and display. LaunchDarkly’s Experimentation team is building one of the company’s most strategic product areas: a platform that helps leading engineering organizations move beyond intuition and make product decisions with real statistical confidence. Sitting at the intersection of large-scale systems, data science, and user experience, the team is creating a best-in-class experimentation product that lets customers set up, manage, and analyze experiments with ease while still earning the trust of even the most rigorous data teams. From warehouse-native analysis to experimentation workflows built on top of LaunchDarkly’s massive feature management scale, this team is tackling ambitious technical problems with visible customer impact and a clear opportunity to define the future of modern software experimentation As the Engineering Manager, you'll bring a balance of people management and technical leadership as you drive the development of the multiple services that power this product and foster a high-performing, collaborative engineering culture. Responsibilities: Lead and develop a team of engineers, providing coaching, feedback, and career growth opportunities Partner with PM and Design to scope, estimate, and sequence roadmap items, making scope tradeoffs in real time. Own the team's delivery of features, ensuring completion within timelines and quality requirements. Collaborate with adjacent teams (Warehouse Integrations, Metrics, and Guardian) on shared infrastructure decisions and cross-team dependencies Communicate roadmaps, risks, and progress clearly to engineering leadership and cross-functional stakeholders Build team working norms that promote collaboration, reduce silos, and keep engineers engaged Drive operational excellence — improve reliabili

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is looking for an IT Systems Engineer to lead the technical side of integrating newly acquired companies into Lyft's IT environment. You'll be responsible for migrating collaboration tools, SaaS platforms, and identity systems from acquired teams into Lyft's stack, with minimal disruption to either side. We're looking for a self-starter who's equally comfortable driving projects independently and partnering with others to get things done. The ideal candidate brings strong attention to detail, creative problem-solving, and a genuine drive to automate processes and improve efficiency across the IT organization. Responsibilities: Manage SaaS integration and consolidation during merger and acquisition activity, ensuring smooth platform migrations, data integrity, and minimal disruption across merged organizations Provide architectural, engineering, and operational support for corporate IT systems at Lyft Support single sign on integrations with Lyft’s primary identity provider, Okta. Leverage various APIs to write scripts and applications to automate IT Operations Support and work with IT, Security and other internal departments by building automation for repetitive tasks Write detailed and concise documentation and runbooks Engage with vendors to implement and improve services to best support Lyft’s needs Be a mentor to others in IT and act as a source for others Experience & Skills: 5+ years of experience managing corporate IT Systems Proven experience supporting IT integration during mergers, acquisitions, or divestitures, including SaaS platform consolidation and system migrations SaaS system application management including but not limited to: Gsuite, Okta, Atlassian, Slack Scripting experience leveraging GAM, Python, Bash, and/or equivalent tools Comfortable consuming RES

Machine Learning Engineer – (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 Experience: 5+ years of industry experience in Machine Learning, with at least 3 years 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 A

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

Machine Learning Engineer We’re looking for a 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 Experience: Multiple years of industry experience in Machine Learning, with at least 3 years 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:

Req ID - FEQ427R59 Location: London The Role As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage. The Impact You Will Have Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins Own frontline technical relationships with customer engineers, data teams, and technical leads Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community What We Look For 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink) Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics Strong presentation and dem

The HD Mapping team is seeking an experienced full-stack engineer to lead development of the web services that support the creation, cataloging, and maintenance of 3D HD maps deployed across Zoox’s fleet. This role will be instrumental in scaling our mapping operations into multiple new cities. In this role, you will: Own and architect backend services (FastAPI) for the HD Mapping team's web infrastructure Support development of frontend tools for interacting with Zoox’s maps (TypeScript, React, MUI, Deck.gl) Automate complex pipelines and workflows Mentor team members on web technologies and distributed systems You will establish guidelines and refactor existing code to follow best practices Qualifications Strong experience in backend development and distributed systems Frontend experience and knowledge of best practices (proficiency in Python, TypeScript, and React) Knowledge of relational database design (Postgres) and RESTful API development Proven ability to lead technical initiatives and mentor others Experience automating complex workflows (Airflow) Bonus Qualifications Experience with FastAPI, Kubernetes, and ArgoCI Knowledge of geospatial data and coordinate systems About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the applica

Location: Mumbai, India (Andheri East) Description: We’re hiring Senior Software Engineers to lead the design and delivery of robust, scalable, and production-grade data systems across a high-growth, multi-venture environment. This is a high-impact leadership role for someone who thrives in hands-on build mode, and who can scale technical delivery without losing speed, quality, or ownership. If this is interesting, we would love to hear from you! About Blenheim Chalcot Blenheim Chalcot India is part of Blenheim Chalcot a global venture builder headquartered in London. With over 26 years of innovation, we've been at the forefront of creating some of the most groundbreaking GenAI-enabled companies. Our ventures lead the charge in digital disruption across a spectrum of industries, from FinTech to EdTech, GovTech to Media, and beyond. Our global presence spans the US, Europe, and Southeast Asia, with a portfolio that employs over 3,000 individuals, manages assets exceeding £1.8 billion, and boasts total portfolio sales of over £500 million. The role We’re hiring Senior Software Engineers to build scalable products, tools, and systems across our portfolio companies. This is a high-impact role for someone who thrives in hands-on engineering, writes maintainable code, and is deeply motivated by solving real-world problems with technology. You’ll work closely with product and engineering colleagues in both Mumbai and London, driving delivery within a specific business. If you're passionate about engineering craft, product-led development, and delivering systems that scale, we’d love to hear from you. Behaviours that we look for Solve problems rigorously , not reactively - breaking them down into tractable elements and considering multiple paths to resolution. Write clean, defensive code with clear structure and minimal complexity. Think about testing and observability early , automating meaningful tests and implementing relevant metri

GAQ426R192 About the Role As Senior Manager, Finance Data and AI, you will lead the team that owns the data foundations, finance semantic layer, financial reporting, and AI-enabled analytics that power Databricks' Finance and Accounting organization. You will report to the Senior Director, Finance Data, AI & Strategy, and serve as the domain and technical anchor for a team that turns financial operations into trusted, well-governed data and reporting. This individual is expected to be based in Bengaluru. This is a high-impact role at the intersection of finance and accounting domain expertise and modern BI/analytics capability. It is less about deep distributed-systems engineering, and more about deeply understanding how Finance and Accounting operate (close, reconciliations, revenue recognition, chart of accounts) and building a trusted data foundations on top of the Databricks platform and Finance DataLake that Finance and Accounting can rely on every day. What You Will Do: Orchestrate jobs using Databricks Jobs and Lakeflow Declarative Pipelines, with built-in data validation and reconciliations, to ensure Finance and Accounting can trust the data behind every report Own and evolve the Finance semantic layer: metric definitions, business logic, and data models that ensure a single source of truth for financial reporting across Finance, Accounting, and the broader business Partner closely with Accounting during month-end and quarter-end close, providing hands-on support to ensure reporting data is accurate, timely, and reconciled, and driving timely resolution of data-related issues Build and maintain dashboards and reporting for monthly, quarterly, and executive-level reporting, translating financial data into decision-ready insight for Finance leadership and the CFO organization Identify, scope, and deliver AI use cases that materially change how Finance and Accounting work day to day, including forecasting automation, anomaly detection, and natural language

Amplitude's Cloud Platform team builds the systems that every Amplitude engineer relies on every day to ship code — and we're rebuilding them for the AI era. As a Staff Platform Engineer, you'll set technical direction for the platform across teams, lead our highest-complexity and highest-leverage initiatives, and shape a platform where AI agents are first-class users alongside humans: kicking off deploys, opening pull requests against infrastructure, and triaging incidents, so a single engineer can get the throughput of a team. You'll operate across team boundaries — partnering with product engineering, fellow Staff+ engineers, and engineering leadership to make Kubernetes and cloud infrastructure effortless across the entire engineering org. You'll build the self-service automation, shared standards, and scalable AWS and GCP infrastructure that let dozens of product teams ship faster, safer, and with less cognitive load — and you'll multiply the engineers around you while you do it. Key Responsibilities Set technical direction — shape platform and domain-level technical strategy that improves developer experience, reliability, security, and cost, and lead the high-complexity, cross-cutting initiatives that deliver it with measurable impact for the organization. Drive clarity through ambiguity. Take on the most loosely-defined problems, validate the critical assumptions early, and create alignment with stakeholders across teams so others can move quickly and confidently — driving cross-team decisions to a timely close and escalating when needed. Build the AI-augmented platform. Design org-wide tooling, guardrails, and policy-as-code that help every engineer get more out of AI-assisted development — infra primitives an LLM can safely reason about and PR against, automated review, and standards that hold as AI changes how code gets written. Own Infrastructure-as-Code standards for Kubernetes, AWS, and GCP using Terraform, Helm, Kustomize, and emerging tooling — setti

Opportunity Get Well (GW RhythmX) is seeking a highly experienced and innovative Staff AI Engineer to lead the architecture, development, and optimization of cutting-edge AI solutions across the organization’s healthcare platform. This role requires deep technical expertise in large language models (LLMs), multimodal AI systems, agentic frameworks, and voice technologies—including STT (speech-to-text) and TTS (text-to-speech). As a Staff-level technical leader, you will guide the AI engineering lifecycle from conceptualization to deployment at scale while serving as a key cross-functional partner to product, engineering, and clinical teams. This is a high-impact, hands-on role for a forward-thinking AI expert with a strong understanding of emerging agentic systems and best practices in safety, observability, and machine learning operations in regulated environments. Responsibilities Healthcare-Focused AI System Design & Development Architect and develop production-ready AI models trained on real-world clinical datasets sourced from hospital systems, EHRs, and patient engagement platforms. Partner with clinical informatics and product teams to derive insights from structured and unstructured health data, including FHIR, HL7, CCDA, and EHR notes. Design and train speech-to-text (STT) and text-to-speech (TTS) models to power voice-enabled AI applications and virtual assistants in a healthcare setting. Integrate and optimize agentic systems using frameworks such as LangChain, LangGraph, or CrewAI for autonomous decision-making and workflow automation. Drive the end-to-end development lifecycle—from data prep and model training to evaluation, deployment, and monitoring—ensuring responsiveness and efficiency in high-impact healthcare settings. Evaluate and incorporate emerging AI technologies and architectural tools to improve intelligence, personalization, and user experience. Infrastructure Optimization & MLOps Lead the model lifecycle from ingestion and p

FEQ427R313 While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered. Sr. Solution Engineers at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark™, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Sr. Field Engineering Manager for the team. Important Eligibility Requirement: Due to contractual requirements supporting U.S. Public Sector customers, this position requires U.S. citizenship. Candidates who are not U.S. citizens are not eligible for consideration. The impact you will have: Partner with the sales team to help customers understand how Databricks can help solve their business problems Provide technical leadership for customers to evaluate and adopt Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present references architectures, how-tos, and demo applications for customers Become an expert in, and promote Databricks inspired open-source projects (Apache Spark™, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars Travel to customers in your region What we look for: U.S. citizenship