Lead Machine Learning Scientist Jobs

Location: United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a Senior AI Platform and Harness Engineer to develop and maintain the infrastructure, tooling, and evaluation frameworks that power enterprise AI solutions. This role is responsible for building the AI platform and reusable "AI harnesses" that enable Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and Generative AI applications to be securely developed, tested, evaluated, monitored, and deployed at scale. The ideal candidate has experience with AI platforms, LLMOps, software engineering, cloud-native technologies, and backend systems, along with a passion for building reliable, observable, and production-ready AI solutions. You will work closely with AI architects, software engineers, data scientists, and product teams to ensure AI solutions are scalable, secure, cost-effective, and continuously improving. What You'll Do: Design, build, and maintain enterprise AI platform capabilities supporting Large Language Models (LLMs), AI agents, RAG, and Generative AI applications. Lead data preparation, training and fine-tuning of LLMs Develop reusable AI harnesses to automate testing, prompt evaluation, model benchmarking, regression testing, and quality assurance. Build AI evaluation frameworks to measure model accuracy, retrieval quality, hallucination detection, latency, throughput, cost, and overall application performance. Implement observability and monitoring solutions for AI applications, including telemetry, tracing, logging, dashboards, and operational metrics. Build and maintain LLMOps pipelines supporting model deployment, versioning, evaluation, experimentation, rollback, and continuous improvement. Design automated workflows for prompt testing, retrieval evaluation, AI system validation, and performance benchmarking. Develop internal tools for prompt management, model experimentation, AI performance optimization, and developer

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior Engineering Manager – Data Science for Truecaller for Business(TfB), you will lead a high-performing team of Data Scientists and Data Analysts driving intelligence, safety, and operational clarity for our enterprise ecosystem. You will sit at the intersection of technical excellence, risk monitoring, and strategic product execution—architecting intelligence engines, shaping risk-mitigation roadmaps, and mentoring top-tier talent. You will be responsible for combining your advanced data science skills with leadership abilities to guide the Data team in solving complex business problems and building data-driven solutions for our enterprise customers. You will partner with leadership on long-term planning and development of the team at large. What you’ll do: Own the overarching Data Science strategy and technical roadmap for Truecaller for Business (TfB). Translate business vision into executable data initiatives, define core KPIs, and drive continuous delivery via agile sprint cycles. Lead the hands-on architecture, scaling, and production deployment of ML models to drive core business outcomes. Serve as the strategic liaison between Data Sc

1KOMMA5° At 1KOMMA5° , we pursue a clear vision: Living on wind and sunlight forever for free . To make this a reality, we are building the energy system of the future with Heartbeat AI. Want to be part of it? We bring together regional craftsmanship and scalable software: We don't think of solar, batteries, heat pumps, and e-mobility as isolated components, but control them as an intelligent, integrated overall system in our virtual power plant. Directly connected to the electricity market – in real time, fully automated. This way, energy is used when it is available from renewables and particularly cost-effective. By 2030, our goal is to transition 1.5 million households to renewable energies. Over 3,000 people are working towards this every day, at more than 80 locations worldwide, from Finland to Australia. Want to take responsibility and build solutions that truly matter? Apply now and help us shape the energy world of tomorrow . Become a part of our mission and learn more about our Product & Tech team! Deine Position We are looking for a Senior Software Engineer - Energy Markets to drive the technical direction of our Energy Markets workstream, with the potential to grow into a lead role. Key responsibilities include: Build and optimize backend services for VPP operations and energy market integrations Design systems at the intersection of backend and data processing pipelines Drive technical decisions and guide fellow engineers on architectural choices Navigate between data engineering, backend engineering, and energy market domains Collaborate with product managers, data engineers, and data scientists across team boundaries Dein Profil The successful candidate will have: Proven experience developing scalable backend solutions with TypeScript Data engineering fundamentals — designing systems bridging backend and data processing Hands-on experience with energy service interfaces (smart meters, optimization, load balancing) Strong knowledge of architectural pat

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap Collaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions WHAT'S REQUIRED Bachelor's degree in computer science, software engineering, or a related technical field At least 5 years of professional software enginee

Who is Artefact? Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact. With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design. What you will be doing? We are looking for a Senior AI Engineer / Technical Consultant to bridge the gap between high-level strategy and technical execution. You will act as a "builder first, consultant second," designing and deploying AI/ML solutions that solve complex business problems for global clients. This role involves end-to-end technical leadership, from initial rapid prototyping (PoCs) to scaling production-ready systems. Key Responsibilities Solution Engineering: Design, implement, and deploy pragmatic AI solutions (ML, LLMs, Generative AI) tailored to specific client business needs. Technical Consulting: Act as a technical advisor to client stakeholders, translating business requirements into scalable technical architectures and guiding them on AI best practices. Prototyping & Production: Build and test Proof of Concepts (PoCs) and transition them into production-ready environments, ensuring security, performance, and maintainability. Architecture & Infrastructure: Design robust AI infrastructure using cloud-native services (AWS, Azure, or GCP) and modern data pipelines. Collaboration: Work within cross-functional teams (Data Scientists, Project Managers, and Strategy Consultants) to ensure the technical feasibility of AI initiatives. Mentorship: Lead project workstreams and

About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com. About Ad Cloud Serving Services Team At Appier's Ad Cloud Team Serving Services Team, we build and maintain the critical systems that power the core of Appier's advertising technology. These systems handle massive, high-concurrency, real-time requests, and ensure the stability, low latency, and high performance of our ad delivery. Our SRE professionals are crucial in guaranteeing these services remain reliable under extreme loads, continuously enhancing product availability and performance through innovation and automation . Responsibilities Lead the design and development of scalable, high-performance, and reliable backend services for real-time ad recommendation, data serving, and core ad tech infrastructure. Drive technical roadmap and ownership for sizable projects, ensuring the delivery of robust and efficient solutions within the Ad Cloud ecosystem. Optimize critical system components for latency, throughput, and resource utilization, including database interactions (e.g., MongoDB sharding, ClickHouse optimizations) and network architecture. Enhance system observability, incident management, and operational excellence by implementing comprehensive monitoring, alerting (e.g., Grafana, Prometheus), and refining production SOPs. Collaborate closely with product managers and scientists to translate business requirements into technical designs and ensure seamless integr

About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com. About Ad Cloud Serving Services Team At Appier's Ad Cloud Team Serving Services Team, we build and maintain the critical systems that power the core of Appier's advertising technology. These systems handle massive, high-concurrency, real-time requests, and ensure the stability, low latency, and high performance of our ad delivery. Our SRE professionals are crucial in guaranteeing these services remain reliable under extreme loads, continuously enhancing product availability and performance through innovation and automation . Responsibilities Lead the design and development of scalable, high-performance, and reliable backend services for real-time ad recommendation, data serving, and core ad tech infrastructure. Drive technical roadmap and ownership for sizable projects, ensuring the delivery of robust and efficient solutions within the Ad Cloud ecosystem. Optimize critical system components for latency, throughput, and resource utilization, including database interactions (e.g., MongoDB sharding, ClickHouse optimizations) and network architecture. Enhance system observability, incident management, and operational excellence by implementing comprehensive monitoring, alerting (e.g., Grafana, Prometheus), and refining production SOPs. Collaborate closely with product managers and scientists to translate business requirements into technical designs and ensure seamless integr

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language

About the Team DoorDash is building the next generation of causal decisioning systems for New Verticals: grocery, convenience, retail, alcohol, pets, flowers, and other emerging categories. These businesses operate in high-dimensional, dynamic marketplaces where every consumer, merchant, item, promotion, substitution, search result, and delivery promise creates a causal question. We are hiring a Principal Machine Learning Engineer to lead the Causal ML pod and establish the technical foundation for company-level causal decisioning. This is a senior technical leadership role for a practitioner who has built consequential causal systems in production and can turn ambiguous business questions into a coherent measurement and decision platform. A central mandate is to define and build a durable company-level causal value metric: a trusted, long-term signal that estimates the incremental value created by product, growth, and marketplace actions. The metric will connect experiments, observational evidence, and production ML so leaders and product teams can compare investments on a common basis while protecting customer experience and marketplace health. About the Role You will set the multi-year technical direction for causal ML, lead the pod’s portfolio and operating model, and remain close to the hardest modeling and systems work. You will be accountable for both scientific credibility and production impact. You’re excited about this opportunity because you will… Lead the Causal ML pod across technical strategy, architecture, execution, and quality. Create a roadmap that joins foundational platform work with high-value product applications. Define the company-level causal value metric and its measurement framework, including the target construct, time horizon, component outcomes, identification strategy, calibration, uncertainty, and guardrails. Build the metric into a decision system that teams can use for product prioritization, experiment readouts, intervention select

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The User and Content Foundations org is responsible for deeply understanding our content, users and their interactions by generating high-quality, reusable signals and insights that power relevance and personalization across the platform. We work at the intersection of distributed machine learning, large multimodal models, data infrastructure, and product adoption to build foundational capabilities that support our partners, including Discovery, Search, Growth, and Ads. We are looking for an experienced Staff Machine Learning Engineer / Technical Lead who can drive the team’s technical direction, lead the team in building scalable content understanding systems, and make an impact on core Pinterest user and business outcomes. In this role, you will lead ambiguous, high-impact scientific and engineering efforts that create reusable represent

ROLE SUMMARY As an AI-enabled strategic scientific leader, you will partner with Oncology Research Leadership to integrate AI-driven strategies that will drive data-informed decision-making across our Oncology Research pipeline. As the AI Portfolio Lead, you will bridge cutting-edge AI/advanced analytics with deep Oncology R&D expertise to guide our portfolio strategy. Working as an individual contributor reporting into the Head, Portfolio Strategy and Program Management, you will analyze and continuously assess Oncology Research projects using AI-driven insights (predictive models, scenario simulations, competitive intelligence) and propose actionable strategies to Oncology Research Leadership. This role is science-focused and spans across discovery and preclinical stage programs, ensuring that our project teams pursue the most promising scientific approaches and mechanisms of action. Your work will directly inform pipeline prioritization and resource allocation decisions, enhancing the quality and objectivity of governance deliberations with robust data. ROLE RESPONSIBILITIES Portfolio Analysis and Insights: Continuously analyze the oncology Research portfolio (ESD through Preclinical) using advanced AI/ML tools and analytics to evaluate each program’s scientific strength, probability of success, and strategic portfolio fit per disease area strategies. Strategy Recommendation: Develop and propose data-driven portfolio strategies (at both project and portfolio levels) to senior leaders and Research governance committee. Use scenario analysis and predictive modeling to highlight optimal project prioritization, pipeline balance, and resource allocation scenarios. AI-Enabled Decision Support: Integrate AI-derived insights (e.g. machine learning predictions, knowl

We at NVIDIA seek an Senior Developer Relations, Automated Synthetic Chemistry Science Lead who can coordinate science streams. This role exists at the crossroads of experimental science, optimization, analytical characterization, AI modeling, laboratory automation, and data infrastructure. It demands a practitioner with a background in research who can lead interdisciplinary science teams and accelerate experimentation without compromising scientific quality. What you'll be doing: Coordinate the operating plan across research priorities, technical execution, and program achievements. Convert research objectives into experimental priorities, parameter-space development, campaign planning, and success criteria. Lead research initiatives encompassing synthetic chemistry, catalysis, process chemistry, machine learning, automated systems, and data processing. Build standardized experimental traces capturing successful and unsuccessful outcomes, metadata, quality-control signals, analytical summaries. Guide AI systems for feasibility assessment, outcome prediction, optimization, scope exploration, and campaign orchestration. Integrate automated experimentation, analytical data streams, data curation, model retraining, and campaign decisions into a closed-loop operating model. Establish science-stream governance: build reviews, decision logs, risk and dependency tracking, quality thresholds, and paths for addressing blocking issues. Prepare recurring workstream readouts for program leadership, including scientific progress, critical decisions, cross-team dependencies, resource needs, and unresolved risks. What we need to see: PhD (or equivalent experience) with 10+ years of hands-on experience in experimental science, chemical engineering, material science, robotics, a

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About the Role Okta is seeking a highly analytical and forward-thinking Global Paid Search Marketing Manager with exceptional Martech integration skills to join our Global Digital Acquisition Team. In this role, you won't just manage campaigns, you will own our search portfolio's evolution. You will be responsible for moving beyond traditional lead-gen metrics to implement advanced Value-Based Bidding (VBB) models that align search spend directly with downstream pipeline value. Leveraging cutting-edge AI capabilities and robust statistical testing, you will maintain complete visibility over all in-market campaigns, ensuring every dollar spent is backed by data and optimized for maximum business impact. Key Responsibilities Value-Based Strategy & Execution: Develop and execute comprehensive, AI-driven paid search strategies across Google Ads and Bing Ads. Lead the transition to and optimization of Value-Based Bidding (VBB) models to prioritize high-value pipeline and revenue over raw lead volume. AI Integration & Innovation: Proactively leverage AI and machine learning capabilities within search platforms (e.g., Smart Bidding, Broad Match + Smart Bidding loops, AI-powered ad assets and campaign types) to scale performance, uncover hidden demand, and push our strategy past the industry curve. Rigorous Experimentation: Design, execute, and analyze structured A/B and multivariate tests (bidding, copy, landing pages). Champion a scientific approach, ensu