Ml Services Software Development Engineer Jobs

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

P-1439 As Applied ML/AI Engineer at Databricks, you will define and create the Agentic Machine Learning revolution. You will help world’s largest companies build and deploy massive classical machine learning solutions (such as personalized recommendations, fraud detection, dynamic pricing, forecasting) fully using Databricks’ agents and harnesses. After 30 years of painfully slow progress, expensive knowledge acquisition and tedious processes in classical ML, the agentic era has ushered innovation, scale and visibility for all: from the most junior data scientists and machine learning engineers to the world class experts. You will work on Databricks’ Genie Code, an agent and an ML “exoskeleton” that is authoring ML, training and deploying models, monitoring and self-healing production ML, all at the top-expert level. Additionally, you will develop ML solutions that under the hood address the most pressing questions non-technical business people have today: predictive and what-if questions. Your work is a top priority for Databricks and you will report to a Principal Software Engineer (a Director level position). The impact you will have: Build agentic end-to-end systems in a small, highly international team of experienced engineers in a flat and agile organization. Build solutions for people like you: software engineers, ML engineers, data engineers, data scientists and MLOps engineers. Own our applied ML investment by engaging with engineering and product teams across the company. Drive the development and deployment of state-of-the-art ML/AI models and systems that directly impact the capabilities and performance of Databricks’ products, infrastructure, and services. Architect and implement robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments. Work on novel forecasting techniques. Possibilities to contribute to the broader AI community by presenting a

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Anyscale is looking for a Site Reliability Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented engineers with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale’s cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers. A snapshot of projects you may work on Design, build, and scale services that orches

Senior GenAI Engineer Location: Charlotte, NC | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial

Senior GenAI Engineer Location: Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions W

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the team The Applied AI Engineering team ensures our customers get the optimal experience from DevRev. As customers go through their DevRev journey, they may identify needs for integration with existing enterprise systems and services, workflow and process automation, or customization of the DevRev platform to achieve their business objectives. Our team works with customers to understand requirements and design, develop, and implement solutions to meet customer goals. Your mission is to systematically help customers find value with DevRev by developing a thorough understanding of their needs, owning coordination between internal and external stakeholders, and engineering the solution to get the job done. You are a product expert and will use your application development and AI/ML skills to ensure our customers get the most out of the DevRev platform. About the role As a Forward Deployed Engineer at DevRev, you will work closely with our post-sales Customer Experience team to help customers unlock value through AI. You will design and deploy intelligent agents, automated workflows, and integrations that transform how customers operate — connecting DevRev to their broader ecosystem and putting AI to work across

Job Requisition ID # 26WD101494 Machine Learning Operations Developer, Inference, AI/ML Platform L'affichage de poste en français suivra / The French job posting follows Position Overview Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking an MLOps Developer to join our AI/ML Platform team. This role will contribute to ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering teams from various domains including design, construction, manufacturing, and media & entertainment to support platform operations. The role is hybrid Toronto or Montreal. Responsibilities Contribute to the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practices Develop and maintain automated deployment pipelines for machine learning models, supporting seamless transitions from development to production Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing <li style="color:#1d

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the team The Applied AI Engineering team ensures our customers get the optimal experience from DevRev. As customers go through their DevRev journey, they may identify needs for integration with existing enterprise systems and services, workflow and process automation, or customization of the DevRev platform to achieve their business objectives. Our team works with customers to understand requirements and design, develop, and implement solutions to meet customer goals. Your mission is to systematically help customers find value with DevRev by developing a thorough understanding of their needs, owning coordination between internal and external stakeholders, and engineering the solution to get the job done. You are a product expert and will use your application development and AI/ML skills to ensure our customers get the most out of the DevRev platform. About the role As a Forward Deployed Architect, you will serve as a hands-on senior technical architect on the Applied AI Engineering team, owning the end-to-end design and delivery of AI-driven business transformation projects. You will work closely with pre-sales teams to scope technical integration and implementation strategies, translating business requirement

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention. As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network. At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale. What you’ll do Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development. Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions. Shape the str

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention. As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network. At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale. What you’ll do Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development. Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions. Shape the str

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention. As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network. At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale. What you’ll do Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development. Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions. Shape the str

Opportunity Overview: We are seeking a Technical, Hands-on Manager to lead a team in building AI-driven healthcare enterprise applications . In this role, you will combine strong people leadership with deep technical expertise to guide the development of scalable, data-intensive solutions that drive meaningful business impact. As a leader who is still technically involved , you will mentor and manage data scientists and analysts while having the ability to guide the team through evaluating, selecting, and implementing the right models , paired with an understanding of end to end workflow and ensure the delivery of scalable AI solutions . This position requires excellent communication and collaboration skills as you partner closely with internal stakeholders and cross‑functional engineering, product, and clinical teams . In our fast-paced environment, adaptability is key—your ability to reprioritize quickly and lead your team through evolving business needs will ensure maximum impact What you’ll do: Lead, mentor, and develop a high‑performing team of Data Scientists and ML Engineers, ensuring strong execution and continuous skill advancement. Contribute to event‑driven architecture design and implementation, enabling asynchronous processing and large‑scale system integration. Work seamlessly across functions—partnering with Data Scientists on model tuning, experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies. Provide technical leadership in the effective use of AWS services such as Lambda, EC2, EMR, S3, Athena, Batch, Textract, Comprehend, Bedrock. Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams. Conduct code reviews, pr

The Opportunity A dobe Brand Intelligence forms the basis of Content Supply Chain, helping enterprises develop, control, and enhance on-brand content at scale . Through the integration of enterprise context, extensive brand knowledge, and AI agents, ABI develops smart workflows that assist global brands in providing flawless and personalized customer experiences across all platforms. We are seeking an exceptionally qualified Principal Scientist to lead the software architecture for ABI. This is an outstanding opportunity for a seasoned software architect to build and scale large, distributed software platforms, transforming AI innovation into production-ready systems. Impact You’ll Make Define the long-term software architecture and technical vision for ABI. Build the foundational platform delivering AI capabilities consistently across Adobe applications, web experiences, and enterprise ecosystems. Drive architectural decisions for backend services, web applications, APIs, and platform infrastructure. Partner with the ML team to operationalize AI models into scalable, secure, enterprise-ready software systems. Direct engineering strategy across multiple teams while offering mentorship to senior engineers and technical leaders. What You’ll Do Define the comprehensive architecture for ABI, including backend services, frontend applications, SDKs, APIs, and integration systems. Architect and build highly scalable distributed systems with high availability, low latency, and operational resilience. Build scalable APIs and platform capabilities that enable seamless connection with Adobe Creative Cloud applications and other third-party platforms. Lead the development of modern web applications and shared frontend frameworks for Adobe Brand Intelligence experiences. Integrate AI capabilities into production through effective orchestration

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist II Role Overview Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps. Key Responsibilities Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components. Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. Build RAG solutions, embeddings workflows, vector-search applications, and AI agents. Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining. Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations. Implement CI/CD, automated testing, observability, model monitoring, and production support practices. Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions. Required Skills & Experience 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field. Strong Python, SQL, object-or