Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future. 

Bready* to make a change?

Toast is looking for a Staff Machine Learning Engineer to serve as a technical linchpin for our AI Platform team. At the P4 level, you aren't just deploying models; you are designing the fundamental infrastructure that enables dozens of teams to build, deploy, and monitor AI at scale. You will act as a force multiplier, mentoring senior engineers and setting the architectural standards for our MLOps lifecycle—from feature stores and automated retraining to high-performance inference at the edge.

About this Roll*:

• Architectural Leadership: Design and lead the evolution of a unified MLOps platform that supports diverse needs across Toast, ensuring high availability, scalability, and security of ML services.
• Engineering Excellence: Champion and institutionalize best practices for CI/CD for ML (MLOps), automated testing, and infrastructure-as-code (Terraform).
• Cross-Functional Synergy: Lead collaborative efforts across Data Engineering, DevOps, and Product teams to bridge the gap between model prototyping and production-grade reliability.
• Strategic Roadmapping: Partner with leadership and Product Managers to define the 1-2 year technical vision for AI infrastructure, prioritizing long-term stability over short-term fixes.
• Operational Ownership: Set the standard for observability and incident response for ML systems, driving root-cause analysis for complex system failures.
• Mentorship: Actively mentor P2 and P3 engineers, fostering a culture of technical rigor and continuous learning.

Do you have the right ingredients*?

• Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
• Experience: A minimum of 10-12+ years of professional software engineering experience, with at least 6-7 years specifically focused on productionizing and scaling ML systems at the enterprise level.
• Core Tech Stack: Expert-level proficiency in Python, Scala, or Java/Kotlin. Extensive experience with PySpark and high-performance computing.
• Generative AI & LLMOps: Proven track record of taking LLM applications from research to production, including experience with Vector Databases, LangChain/LangGraph, and A2A protocols.
• System Design: Superior ability to design distributed systems that handle millions of requests with sub-second latency.
• Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
• Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration, MLflow
• Profound knowledge of model deployment, orchestration (Apache airflow, Prefect), scaling, and managing CPU/GPU resources efficiently. 
• Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach. 
• Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
• Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable

Bonus Ingredients (The "Staff" Edge)

• Data Strategy: Experience implementing enterprise-grade Feature Stores (e.g., Tecton, Feast) and real-time streaming frameworks like Apache Flink or Ray.
• Full-Stack Visibility: Ability to dive into the UI/UX layer (React) or deep into the kernel/networking layer to debug performance bottlenecks.

Open Source/Community: Contributions to relevant open-source projects (MLflow, Kubeflow, etc.) or a history of speaking at industry conferences.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

Position Summary:

We are looking for a Staff Software Engineer – Full Stack & AI Innovation with strong hands-on experience in TypeScript (Node.js, JavaScript), and/or Python and a passion for leveraging AI-driven code generation tools to accelerate development. You will play a critical role in operationalizing GenAI-based code generation platform. This role involves translating product specifications into structured inputs for GenAI tools, reviewing the code generated by GenAI tool, and providing feedback to product engineering team to improve quality and performance of the GenAI tool.

You will work closely with product managers, software engineers, and AI specialists to ensure that the generated code aligns with business and technical requirements. The ideal candidate is curious, adaptable, critic and eager to evaluate AI-assisted code generation tool.

Key Responsibilities:

• Develop, Analyze and structure product specifications for input into GenAI programming tools.
• Operate GenAI systems to generate code based on structured inputs.
• Perform detailed code reviews of GenAI-generated programs to ensure correctness, performance, and maintainability.
• Utilize several other AI-powered code generation tools (Cursor.ai, Windsurf, etc.) to compare and optimize GenAI tool in subject.
• Provide feedback to improve GenAI model outputs and prompt engineering strategies.
• Review and validate generated code for correctness, efficiency, and adherence to coding standards.
• Maintain documentation of input formats, code review findings, and feedback cycles.
• Stay current with advancements in GenAI programming tools and code generation technologies.
• Participate in code reviews and mentor junior developers.

Basic Qualifications:

• Bachelor’s/master’s in computer science, Engineering, or equivalent experience.
• 8 to 10 years' experience with strong expertise in at least one of the following:
• TypeScript / JavaScript (Node.js, React, Next.js, Angular, Vue.js)
• Python (Django, Flask, FastAPI/ RestAPI)
• Person must have designed, developed, and maintained scalable front-end and back-end applications using TypeScript/JavaScript/Python.
• Solid understanding of front-end technologies (HTML5, CSS3, Tailwind, Material UI or similar).
• Familiarity with GenAI tools and LLM-based code generation platforms (e.g., GitHub Copilot, CodeWhisperer, etc.).
• Experience with databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB).
• Hands-on experience with Cursor.ai and/or Windsurf (plus other AI-assisted coding tools like GitHub Copilot, Tabnine, Codeium).
• Strong understanding of software development principles and code review practices.
• Familiar with Code review tools (e.g. GitHub, GitLab, Bitbucket etc)
• Strong grasp of software design principles (OOP, SOLID, microservices).
• Excellent problem-solving, debugging, and collaboration skills.
• Excellent analytical and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications:

• Experience working with prompt engineering or structured input design for GenAI systems.
• Exposure to MLOps or AI model evaluation frameworks.
• Knowledge of software architecture and design patterns.
• Knowledge of containerization (Docker, Kubernetes).
• Exposure to serverless architecture and event-driven systems.
• Contribution to open-source or AI-driven development communities.

Key Responsibilities

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.

Required Qualifications

• Strong understanding or experience leading AI/ML teams in a SaaS or enterprise software environment.
• Deep expertise in time series forecasting and machine learning.
• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
• Experience with agentic frameworks and autonomous agent architectures.
• Proficiency in Python and modern software development practices (testing, code review, CI/CD).
• Proven track record of delivering complex technical projects on time with high quality.
• Excellent communication, collaboration, and stakeholder management skills.
• Track record of delivering impactful AI solutions in a fast-paced, agile environment.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
• Experience with large-scale data processing frameworks like Spark.
• Familiarity with the challenges of applying AI in enterprise planning or financial domains.
• A portfolio of published research or contributions to open-source AI projects.

What Makes This Role Exciting

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.

Sobre a vaga e missão do cargo 

Você fará parte do nosso time de Precificação e atuará com projetos de ciência de dados.

No seu dia a dia, você vai: 

• Desenvolver, validar e manter modelos preditivos e analíticos que apoiem decisões estratégicas do banco;
• Traduzir problemas de negócio em hipóteses e modelos quantitativos;
• Realizar análise exploratória de dados (EDA) e engenharia de features;
• Avaliar performance, estabilidade e viés dos modelos;
• Documentar modelos de forma clara e auditável;
• Apoiar a implementação e monitoramento contínuo dos modelos em produção;
• Apresentar resultados de forma clara para públicos técnicos e executivos.

O que buscamos 

Obrigatórios:

• Graduação completa em Estatística, Ciência da Computação, Economia ou áreas correlatas;
• Protagonismo, visão crítica e capacidade de comunicar resultados técnicos de forma clara para diferentes níveis de público;
• Sólida experiência com modelagem preditiva e estatística aplicada;
• Domínio de ferramentas analíticas e linguagens como Python e SQL;
• Forte habilidade em manipulação de dados e validação de modelos;
• Capacidade de documentação técnica e organização;
• Conhecimento em controles de versão (git);
• Boas práticas de programação e organização de código.
• Será diferencial se tiver experiência prévia em precificação e/ou no setor financeiro;
• Conhecimento em plataformas de Cloud (preferencialmente AWS).

Desejáveis:

• Conceitos de MLOps;
• Deploy de modelos;
• Re-treinamento automatizado;
• Containers (Docker) e APIs;
• Experiência em instituições financeiras;
• Experiência em projetos de precificação.;
• Atuação prévia com dados críticos (risco, crédito, liquidez);
• Experiência em escalar soluções de dados do piloto à produção;
• Conhecimento prático em governança de dados.

Benefícios 

• Vale-alimentação e Vale-refeição;
• Plano de saúde e odontológico;
• Seguro de vida;
• DayOff de Aniversário;
• Baby On Board e Sala de Amamentação;
• Licença parental estendida;
• Auxílio-creche/babá e/ou auxílio para filhos com deficiência;
• Wellhub e Grupo de Corrida Inter;
• Espaço CARE4U (Belo Horizonte): serviços de autocuidado com valores exclusivos, área de descompressão, jogos e minicampo de golfe;
• Vantagens no nosso SuperApp, como Duo Gourmet;
• Cartão Prime Inter;
• Programas de treinamento e capacitação internos.

Etapas do Processo Seletivo

• Triagem de currículos;
• Screening (abordagem inicial para alinhamento de expectativas sobre a vaga);
• Assessments;
• Entrevista com Time de Talent; 
• Teste técnico (quando necessário);
• Entrevista com a liderança;
• Proposta de Contratação (Offer).

P-226

As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.

The impact you will have:

• Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.  
• Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems
• Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains
• Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving, to model monitoring, all within a single platform, as well as participating in the larger ML SME community in Databricks
• Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, helping with the adoption of Databricks’ AI offerings

What we look for:

• 5+ years of hands-on industry ML experience in at least one of the following:
• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
• AI Engineer: Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through ML & AI
• [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role
• Can meet expectations for technical training and role-specific outcomes within 3 months of hire
• This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Manager AI/ML Ops Engineering, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Focus on team members and coaching them to play to their strengths, grow and deliver peak performance
• Lead and mentor a team of AI/ML Ops engineers and operations specialists.
• Define and govern solutions for AI/ML operations, ensuring scalability, cost-efficiency, and reliability
• Develop and maintain standardized AI/MLOps workflows, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines
• Delegate and harness the aggregate strength of your team.
• Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values.
• Actively helps individuals and the overall team to set priorities and focus on delivery of commitments
• Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security
• Lead and facilitate cross-team interactions, communication, and dependencies
• Ensure all changes are fully tested before being deployed
• Ensure deployment plans are well-considered and include appropriate scalability and load tests
• Work with stakeholders to align AI projects with business strategies.
• Ensure all AI/ML Ops solutions adhere to regulatory compliance, security, and ethical guidelines
• Drive Engineering and Operational excellence initiatives
• Perform other duties as assigned
  
  

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Experience building teams through recruiting and retention
• Experience in Leading and Mentoring a team of ML engineers and operations specialists.
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.

You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. 

You Will:

Model and Pipeline Automation 

• Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. 
• Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
• Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.

Governance & Compliance

• Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.

Performance Monitoring

• Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. 
• Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.

Cross-Functional Collaboration

• Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
• Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.

Architecture and Infrastructure Management

• Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
• Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
• Distill complex ML concepts into easy-to-follow technical documentation.

You Have:

• 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 
• 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
• 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
• Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. 
• Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
• Experience developing, documenting, and supporting REST APIs
• A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Principal Data & AI/ML Ops Engineers, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. 

You Will:

• Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
• Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
• Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
• Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
• Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python, SQL, and potentially Java or Scala
• Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Driving engineering excellence initiatives
• Legally eligible to work in India on an ongoing basis

About the Role

We're hiring an AI Engineer to work on the AI core of Mill Commercial — the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera and onboard compute directly into our high-capacity food recycler; models running on the edge identify, classify, and quantify food scraps at the point of generation, and our vision pipeline turns that signal into procurement and operational guidance for large food service operators.

You'll join a small AI team, building the data and training pipeline that produces our edge CV models, designing the cloud-side evaluation that tells us whether those models are good enough to ship, and helping build the agentic, LLM-driven product features that turn raw waste data into customer-facing insights and recommendations. This is a hands-on senior IC role for someone who's equally comfortable fine-tuning a segmentation model, prompting a VLM, and wiring an agent into a product feature.

What You'll Do

• Build and manage the end-to-end ML training pipeline: data ingestion from deployed kitchen units, ground truth generation, annotation tooling (including foundation-model-assisted labeling), training, evaluation, and retraining cycles.
• Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline — from prompting foundation models to fine-tuning ConvNets and VLMs.
• Build the cloud-side evaluation harness that tells us how our shipped edge models are actually performing in the field — automated, reproducible, and aligned to product accuracy targets across food types, kitchen environments, and deployment configurations.
• Own MLOps: reproducible training, experiment tracking, model versioning, and automated evaluation against product-defined accuracy targets.
• Export and validate models for deployment to edge devices, working closely with the edge team on optimization, quantization, and integration.
• Help design and build the LLM- and agent-powered product features that consume waste characterization data and turn it into customer-facing recommendations — purchasing suggestions, anomaly explanations, operational nudges. Define how agents call tools, ground in customer data, and stay reliable in production.
• Analyze failure cases systematically — unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions — and drive the data and modeling decisions that close accuracy gaps.

What We're Looking For

• Strong fundamentals in computer vision and deep learning — segmentation, detection, classification, tracking. You understand the architectures well enough to make informed choices.
• Fluency with modern ML approaches — VLMs, LLMs, foundation models, and agentic systems — alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product.
• Experience building ML training pipelines and data annotation systems at scale.
• Experience evaluating ML models rigorously — designing metrics, building the eval harness, and using results to drive product decisions rather than just publish a number.
• Proficiency with cloud ML infrastructure (AWS or equivalent) — you've managed training jobs, data pipelines, and experiment workflows in production.
• Familiarity with cloud-to-edge model deployment.
• Clear, direct communication — you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow.
• Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission.

Software skills: Python, PyTorch, OpenCV. Strong familiarity with MLOps on AWS infrastructure. Experience with LLM and agent frameworks. Google Cloud / Gemini experience is a plus.

Nice to Have

• Experience with video understanding (temporal consistency, tracking, video segmentation)
• Experience with foundation models for data annotation
• Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents)
• Experience shipping LLM- or agent-powered features in a consumer or B2B product
• Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems

The estimated base salary range for this position is $240 to $280k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Data Analytics Team Lead   

Our organization is highly regarded as the industry leader in providing physical therapy/rehabilitation outpatient services.  We have an immediate opening for a Data Analytics Team Lead. We offer a very comprehensive benefit package including Medical, Dental and Vision Insurance, Life Insurance, 401k retirement plan with a company match, generous paid time off (PTO), and much more.  

Team Size: 4–6 (Analysts, Data Engineers, BI Developers)  

Location(s): 100% remote. Preferred locations are Nashville - Chattanooga, TN or greater DFW area, TX.  

We are seeking a strategic and investigative Data Analytics Team Lead to accelerate our journey from reporting to predictive and prescriptive intelligence - unlocking insights that improve patient outcomes, optimize clinic performance, and fuel enterprise growth. Someone who goes beyond the problem and is passionate about identifying and resolving the root case.

You will own Upstream’s enterprise data, analytics, and AI strategy, leading a high-impact team to deliver actionable intelligence across clinical, operational, financial, and patient experience domains. This is a player-coach role: you’ll architect solutions, mentor talent, and translate complex data into executive ready narratives - all while driving measurable ROI.  

The successful candidate will have a thorough working knowledge and understanding of every aspect of Upstream's business operations. They will create dashboards and reports that transform raw data generated by various sources into actionable information that decision makers need to successfully perform their daily duties.  Refined social and communication skills are required that enable effective collaboration with business executives, managers, stakeholders, and subject matter experts, regardless of their level of expertise or technical skills. They must be able to play multiple roles, including architect, report developer, metadata modeler, SQL programmer, and end-user trainer and mentor.  

Success looks like:  

• Reducing claim denial rates by 15% via predictive denial modeling  

• Increasing patient retention by 8% through propensity-to-churn analytics - Delivering 90%+ dashboard adoption among regional directors within 6 months  

DUTIES AND RESPONSIBILITIES:  

The Data Analytics Team Lead will be responsible for:  

Strategy & Vision  

• Define and execute a 3-year analytics roadmap aligned to revenue, cost, and quality KPIs  

• Champion AI/ML adoption (e.g., demand forecasting, therapist scheduling, outcome prediction)  

• Establish data governance, lineage, and quality frameworks (in partnership with IT)  

Team Leadership & Culture  

• Lead, mentor, and grow a team of 4–6 analysts and engineers  

• Build a self-service analytics culture via training, templates, and “Analytics Office Hours”  

• Foster cross-functional partnerships (Clinical, Revenue Cycle, Operations, Finance)  

Delivery & Execution  

• Design and deploy enterprise dashboards, predictive models, and automated insights using Microsoft Power BI + Fabric  

• Integrate data from EHR (RainTree), RCM, etc.  

• Own the full BI lifecycle: requirements → pipeline → visualization → storytelling → adoption  

• Implement real-time analytics (e.g., clinic capacity, no-show prediction) using Azure Data Lake + Synapse  

Innovation & Experimentation  

• Pilot GenAI use cases (e.g., automated narrative reporting, patient summary generation)  

• Explore data mesh architecture for clinic-level autonomy with enterprise governance Performing other duties as assigned.  

REQUIRED EXPERIENCE & SKILLS  

• 8+ years in data analytics, BI, or AI strategy (healthcare or multi-site operations preferred)  

• Expert in Power BI (DAX, Power Query, Row-Level Security, AI visuals, performance tuning)  

• Advanced SQL; proficient in Python (ex: pandas, scikit-learn) or R  

• Hands-on with Microsoft Fabric (Dataflows, Lakehouse, Real-Time Intelligence)  

• Experience with data integration (APIs, ETL/ELT, dbt), data lakes, and real-time pipelines  

• Proven ability to influence executives and train non-technical users  

Nice-to-Have  

• Master’s in Data Science, MIS, or HCI  

• Exposure to healthcare data standards (HL7, FHIR)  

• Experience with RainTree EHR  

• MLOps familiarity (Azure ML, GitOps, etc.)  

• Change management or Agile coaching  

EDUCATION  

Bachelors in computer science, MIS, Statistics, or related field. Equivalent experience accepted.  

TRAVEL REQUIREMENTS:  

Occasional travel to other offices, third-party vendors, or educational conferences may be required.  

Preferred System Experience: Raintree, Waystar, Excel, MS Dynamics, Azure Data Factory, APIs, Azure Data Lake Gen2, Fabric Lakehouse, Databricks, Synapse Analytics, dbt, Power BI, Fabric AI,  

Azure ML, Copilot 

JOIN US!  

If you’re a strategic builder who geeks out on turning rehab data into revenue and lives changed, let’s talk.  

Follow @Lifeatupstream on Instagram, and check out our LinkedIn company page to learn more about what it’s like to be part of the #upstreamfamily.

CLICK HERE TO LEARN EVEN MORE ABOUT UPSTREAM

Cherchez-vous à vous épanouir dans un environnement de travail stimulant? 

Joignez-vous à Levio, un leader de la transformation numérique, et propulsez votre carrière vers de nouveaux sommets. Vous travaillerez aux côtés de professionnels de haut calibre sur des projets technologiques ambitieux et de grande envergure, directement intégrés dans les environnements de nos clients. Chez Levio, nous valorisons l’expertise, la curiosité et l’amélioration continue  et nous vous offrons l’espace nécessaire pour évoluer.

À propos du rôle 

Nous sommes à la recherche d'un Analyste fonctionnel IA (MLOPS/LLMOPS) afin de contribuer à des projets d’envergure. Il travaillera dans un environnement infonuagique Azure s’appuyant sur l’Infrastructure-as-Code (IaC), la configuration-as-code (CaC) et le déploiement continu (CD).
Il est capable de traduire des besoins d’affaires en spécifications fonctionnelles et non fonctionnelles détaillées, permettant le développement, la configuration et l’évolution des solutions analytiques. Ils participent également à la stratégie qualité et à son application dans un contexte de moyenne à grande envergure.

Pourquoi rejoindre Levio? 

• Travailler sur des projets de transformation numérique complexes et à fort impact
• Collaborer avec des équipes multidisciplinaires expérimentées
• Développer continuellement votre expertise technique et professionnelle
• Profiter de flexibilité, d’autonomie et d’une culture axée sur l’humain
• Faire partie d’une organisation qui valorise la diversité, l’inclusion et l’innovation

Rôle et responsabilités 

• Analyser en profondeur les cas d’usage analytiques existants (sources, transformations, règles métiers, pipelines, rapports, modèles)
• Documenter l’état actuel (as-is) et définir l’état cible (to-be) adapté à la PDM
• Récolter les besoins et analyses des nouveaux cas d'usages (sources, transformations, règles métiers, pipelines, rapports, modèles)
• Identifier les dépendances, impacts et ajustements requis
• Définir les spécifications fonctionnelles nécessaires à la construction des cas dans notre plateforme de données
• Soutenir les équipes techniques dans l’intégration et la validation
• Assurer la traçabilité entre l’ancien et le nouveau fonctionnement
• Participer à la stratégie d’essais et à la validation fonctionnelle
• Collaborer avec les équipes BI, IA, Data Engineering et Infrastructure

Qualifications et expérience 

• Connaissance des architectures analytiques (data lake, entrepôt, ETL, pipelines)
• Connaissance des concepts MLOps et LLMOps
• Connaissance approfondie des Services ML/AI : Azure ML, Azure OpenAI, Cognitive Services, Azure Search
• IA générative et NLP (fine-tuning, prompt engineering, intégration de modèles)
• Connaissance de Python (requis), R (un atout)
• Expérience Databricks (contexte AI/ML, atout)
• Expérience en analyse d’existant, migrations technologiques ou reverse engineering fonctionnel
• Compréhension approfondie des règles métiers et transformations de données
• Familiarité avec les plateformes analytiques, BI
• Connaissances SQL 

Avantages sociaux 

Levio offre un programme d’avantages sociaux complet et flexible conçu pour soutenir votre développement professionnel et votre bien-être personnel, incluant :  

• 4 semaines de vacances cumulatives dès le premier jour  
• Horaire de travail flexible  
• Allocation de développement professionnel (PDA) pour la formation, l’équipement informatique et les activités physiques  
• Formations adaptées à vos domaines d’expertise  
• Régime enregistré d’épargne-retraite (REER) avec contribution de l’employeur jusqu’à 3 % du salaire brut  
• Régime d’assurance collective modulable  
• Remboursement du transport en commun ou du stationnement lorsque requis  
• Primes de référencement  
• 11 jours fériés  
• Journées personnelles  
• Vie sociale active (5 à 7, club social, collations santé, café, et plus encore)

Détails du poste 

• Type d’emploi : Temps plein, permanent

Équité en emploi

Levio souscrit au principe d'équité en emploi et applique un programme d'accès à l'égalité en emploi pour les femmes, les autochtones, les minorités visibles, les minorités ethniques et les personnes en situation d’handicap. 

Levio valorise la diversité et de l’inclusion et vise à créer un milieu de travail sain, accessible et gratifiant qui met en valeur la contribution unique de nos employés au succès de notre entreprise. En tant qu'employeur qui s'engage à respecter l'équité en matière d'emploi, nous encourageons les candidatures les plus diverses. Des accommodements sont disponibles sur demande pour les candidats qui participent à tous les aspects du processus de sélection. 

Le genre masculin est utilisé sans aucune discrimination et dans le seul but d’alléger le présent texte.  

We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.

This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.

We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.

What you will do: 

• Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
• Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
• Ensure that our data platform and processes meet privacy, compliance, and security requirements.
• Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
• Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
• Write code, mostly in Python and SQL  with occasional additions Typescript, Java or some other language.

We would love to have you on our team if you have:

• 5+ years of experience developing and operating production systems.
• Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
• Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
• Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
• Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
• Demonstrated skills in writing well-structured, testable, and high-performance code.
• Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
• You are self-motivated, proactive, and able to lead and manage your own work effectively.
• A pragmatic and goal oriented approach to development.

What Makes You Stand Out

• Real-life experience with Databricks.
• Familiarity and experience with the Data Mesh approach
• Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 $172,550 - $203,000
• Region 2 $159,000 - $187,000
• Region 3 $148,000 - $174,000

A recruiter can determine your zones/tiers based on your US location.

About the Role

The Platform Infrastructure team at iCapital plays a critical role in ensuring that both production and development environments operate smoothly, securely, and reliably. This role leverages advanced cloud capabilities to support the Platform Infrastructure strategy of market agility and lean operating principles, with a strong emphasis on quality to meet the ever‑growing demands of our clients.

We are seeking highly collaborative, creative, and intellectually curious MLOps/DevOps Engineers with deep expertise in machine learning operations, cloud infrastructure, CI/CD automation, Kubernetes, and security. This role requires hands‑on experience designing, building, and operating scalable DevOps and enterprise‑grade MLOps platforms, including model lifecycle automation, observability, and governance.

As a Platform Engineer, you will wear multiple hats in a highly visible role, partnering closely with engineering, security, data, and business teams to deliver secure, reliable, and highly automated platforms that support both application and machine‑learning workloads.

Responsibilities

• Design, build, and operate MLOps pipelines supporting the full ML lifecycle (training, validation, deployment, monitoring).
• Enable production workloads for AI/ML and Generative AI systems, including LLM‑based services.
• Develop and maintain CI/CD pipelines for AI/ML services and supporting infrastructure.
• Build and manage cloud‑native infrastructure on AWS, with heavy use of Kubernetes and containerized workloads.
• Automate infrastructure provisioning and configuration using Infrastructure as Code (Terraform).
• Implement model versioning, experiment tracking, and artifact management across environments.
• Ensure reliability, scalability, observability, and cost efficiency of AI platforms.
• Partner with AI/ML engineers to operationalize models and standardize deployment patterns.
• Implement monitoring and alerting for system health, model performance, and drift.
• Enforce security, compliance, and governance requirements for AI workloads.
• Participate in incident response, root cause analysis, and continuous improvement initiatives.
• Document standards, best practices, and reference architectures for MLOps and AI infrastructure.

Required Qualifications

• 15+ years of experience in DevOps, SRE, or Platform Engineering, with AWS as a primary cloud.
• Experience supporting machine learning systems in production, including deployment and monitoring concerns.
• Hands‑on experience with machine learning platforms, particularly AWS SageMaker (required).
• Strong hands-on experience with Kubernetes, containerized workloads, and cloud networking.
• Proven experience building and operating CI/CD pipelines (e.g., GitLab CI, ArgoCD).
• Strong proficiency with Terraform and scripting/programming in Python or similar languages.
• Solid Linux, systems, and troubleshooting fundamentals.
• Excellent communication skills and ability to work across teams.
• Direct experience with MLOps platforms and tooling (model registries, experiment tracking, feature stores).
• Exposure to Generative AI / LLM workloads in production environments.
• Familiarity with data stores commonly used in ML systems (e.g., Postgres, DynamoDB, object storage).
• Experience operating in regulated or fintech environments.
• Background in cost optimization for compute‑intensive workloads.
• Strong written and verbal communication skills.
• AWS certifications are a plus.

Benefits

The base salary range for this role is $180,000 to $230,000 depending on experience.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics

Principal Engineer

Location: Waterloo, London, England, UK | Hybrid (1 day per week in office)

Who We Are 

At 8th Light, we bring life to the best ideas.

Founded in 2006 and headquartered in Chicago, we are a technology solutions provider that partners with organizations to solve meaningful challenges and drive sustainable growth. From early-stage startups to global enterprises, we work across industries to optimise our clients’ digital products through product strategy innovation, experiential design, AI solutions, and deep engineering expertise. 

Our commitment to quality means we deliver solutions we’re truly proud of, while our curiosity sparks innovation and breakthrough thinking. 8th Lights thrive in an environment that champions continuous education, fueling our growth through mentorship and hands-on work. We foster an open, collaborative culture grounded in honesty that builds trust, and believe true success is measured by the outcomes we create for our clients.

If this kind of work and our kind of people energizes you, you’ve found the right place. 

Who You Are

You’ve shown long-term repeated success on a variety of projects, typically over the course of 10+ years. You are a trusted expert and leader, often called upon to guide ambiguous initiatives and architect scalable solutions. You bring a blend of deep consulting acumen, technical expertise, and product thinking that drives measurable and impactful outcomes. In your previous experience, you have:

• Demonstrated long-term success on high-stakes consulting engagements across multiple language paradigms, stacks, ecosystems, technical environments, and client industries 
• Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients you’ve served 
• Led the development and delivery of production-grade software using a variety of languages and frameworks, including but not limited to: Python, Java, JavaScript, TypeScript, React, Ruby, Scala, R, SQL, and Go
• Evaluated and strategically applied AI-assistive development tools to accelerate delivery and improve quality
• A track record of understanding, assessing, and embracing new tooling and trends within the software industry
• Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) 
• Used context-appropriate automated testing to inform software design choices and catch bugs
• Successfully led modernization efforts to align legacy systems with short and long-term business needs
• Remedied architecture-level concerns such as scalability, security, reliability, and performance
• Facilitated alignment and collaboration across technical and non-technical stakeholders to move initiatives forward in the face of ambiguity and complexity while balancing technical considerations with product and user needs
• Provided mentorship and team support at scale, while sharing knowledge and improving team practices 
• Actively sought out and effectively given feedback
• Collaboratively led stakeholders to balance technical considerations with product and user needs

What You’ll Do At 8th Light

As a go-to technologist and strategist within 8th Light, you’ll work with a variety of clients, typically one to two in a year, while continuing to deepen your and our collective domain expertise over the course of your career with us. You’ll be responsible for:

• Rapidly building trust with clients, demonstrating technical expertise and understanding of their domain and objectives 
• Guiding technical direction, solving complex problems, and demonstrating best practices while remaining deeply engaged within the codebase
• Working pragmatically to balance technology choices while delivering high-quality work within deadlines
• Advising clients on architecture, scalability and platform evolution, connecting technical decisions to product and business outcomes
• Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring
• Driving innovation by proactively surfacing new technical approaches and product solutions
• Leading or initiating formal feedback conversations with teams and clients via retrospectives
• Clearly articulating and documenting outcomes and driving forward action items
• Contributing to the health of your team and 8th Light’s culture by modelling our Values
• Designing and managing high-level technical roadmaps for large engagements
• Building your network and maintaining relationships with clients and other industry leaders within your domain
• Coaching client engineering teams, transferring knowledge and leveling up practices
• Influencing client CTOs and executive decisions. Planning and execute technical work that involves stakeholders outside of project boundaries such as across a client's technical organization
• Participating in account planning; opportunity identification.
• Facilitating retrospectives, strategy sessions, and technical deep-dives to improve team and project outcomes
• Identifying, mitigating, and resolving blockers to team progress
• Contributing to 8th Light by serving as a mentor, leading or designing workshops internally or for clients, representing 8th Light in the tech community, or supporting our hiring processes
• Demonstrating leadership in scalable system design, modular architecture, and platform- or product-oriented development.
• Bringing depth in testing strategies, observability, fault tolerance, and secure engineering practices.
• Applying architectural patterns to evaluate tradeoffs and drive clear, documented design rationale.

Strongly Preferred Skills

We work across many areas, and encourage anyone with the experience listed above to apply. We would particularly like to encourage applicants with experience in the following areas:

• Delivering and advising on enterprise-grade AI systems, including RAG pipelines, vector search, and agentic frameworks (e.g., LangChain, LlamaIndex, Crew AI, AutoGen, n8n), ensuring scalable, production-ready solutions that empower developers and align with business outcomes.
• DevSecOps & DevOps
• MLOps
• Infrastructure as Code
• Data Engineering: including platforms like Databricks for data processing and analytics.

Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and we’re excited to keep learning and growing together. We have a proud tradition of hiring talented colleagues with real-world career experiences. 

How You’ll be Supported

At 8th Light, we believe our people are our greatest asset. Their growth, well-being, and success shape our future. 

• Our wellness package is designed with the Whole YOU in mind and includes:
• A robust L&D programme featuring unlimited access to thousands of books, courses, and expert-led training on the O'Reilly learning platform.
• Annual financial stipend and time allotment for learning & development
• Coworking support for our global team
• 12 weeks of new parent leave available for eligible employees

See our full list of Benefits. 

A Note on Compensation

At 8th Light, we are committed to a compensation philosophy that is transparent, fair, and helps us attract and retain top talent in alignment with our company’s strategic growth goals and clients’ needs.

We benchmark our salaries using Geographic Structures to establish competitive pay ranges within the regions where 8th Lights live. Our pay ranges for our Principal Engineer position within London is: £92-818-£116-122 GBP

Reach out to recruiting@8thlight.com for more relevant information pertaining to your local market.

8th Light Hubs and Geographies

8th Light's culture is rooted in strong connections that extend across our teams, regions, and beyond client work. We are a distributed team across the United States, Canada, and the United Kingdom, with hubs in Chicago, London, Los Angeles, New York, and Seattle. 

• London Co-working: Employees working from our London hub follow a hybrid model, which includes a minimum of one day per week in our Waterloo Office. This co-working day is designed to encourage collaboration and further strengthen our community.In most cases, our consulting engagements do not require travel.

We hope to see you apply! 

^#LI-Hybrid

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

To be successful in this role, you should possess the following qualifications and skills:

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.

Observability: 5+ years of experience working with observability tools, defining SLOs, designing alerts, dashboards and escalation chains.

• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organisational & Communication Skills: Self-organiSed with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

#LI-FP1

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.
• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Observability: 5+ years of experience working with observability tools, and defining

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organizational & Communication Skills: Self-organized with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.
• Language: English proficiency is mandatory.

#LI-Remote

#LI-DC1

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.
• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Observability: 5+ years of experience working with observability tools, and defining

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organizational & Communication Skills: Self-organized with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.
• Language: English proficiency is mandatory.

#LI-Remote

#LI-DC1

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

To be successful in this role, you should possess the following qualifications and skills:

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.

Observability: 5+ years of experience working with observability tools, defining SLOs, designing alerts, dashboards and escalation chains.

• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organisational & Communication Skills: Self-organiSed with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

#LI-FP1

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

To be successful in this role, you should possess the following qualifications and skills:

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.

Observability: 5+ years of experience working with observability tools, defining SLOs, designing alerts, dashboards and escalation chains.

• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organisational & Communication Skills: Self-organiSed with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

#LI-FP1

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.
• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Observability: 5+ years of experience working with observability tools, and defining

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organizational & Communication Skills: Self-organized with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.
• Language: English proficiency is mandatory.

#LI-Remote

#LI-DC1

Seu desafio no time:

Estamos construindo a nova geração de produtos de Inteligência Artificial da RD Station. Buscamos uma pessoa desenvolvedora Full Stack com foco principal em backend Python, capaz de atuar em sistemas distribuídos, integrações e aplicações internas de IA. Essa pessoa fará parte de um time multidisciplinar com cientistas de dados, engenheiros de IA e desenvolvedores backend e frontend, utilizando principalmente Python e React. O contexto da área ainda está em evolução, então buscamos alguém com perfil proativo, confortável em ambientes de construção e que consiga transitar entre diferentes problemas técnicos conforme a necessidade do time.

Suas principais entregas:

• Desenvolver e manter aplicações em Python com foco em qualidade, escalabilidade e sustentação operacional;
• Contribuir no desenvolvimento frontend utilizando React em fluxos e interfaces do produto;
• Projetar e evoluir APIs e integrações entre serviços e plataformas internas;
• Apoiar a construção de arquiteturas que suportem agentes, automações e aplicações de IA;
• Contribuir para boas práticas de engenharia, documentação técnica e padronização de desenvolvimento;
• Apoiar a definição de estratégias de teste para fluxos com LLMs, agentes e pipelines de IA.

Perfil que buscamos:

• Experiência sólida com desenvolvimento backend em Python;
• Experiência prática em projetos utilizando React;
• Boa base em engenharia de software, arquitetura e design de APIs;
• Domínio de fundamentos de engenharia de software, como SOLID e design patterns;
• Conhecimento em sistemas orientados a eventos e bancos de dados (SQL e/ou NoSQL);
• Facilidade na documentação de código e na criação de diagramas (ex.: UML).

Será considerado um diferencial:

• Experiência com IA aplicada, especialmente envolvendo LLMs, engenharia de prompt, MLOps ou LLMOps;
• Experiência com observabilidade e monitoramento (ex: Datadog);
• Conhecimento em mensageria e processamento assíncrono (Kafka, Pub/Sub, etc.);
• Interesse em explorar aplicações práticas de IA em produtos SaaS;
• Ser (ou querer se tornar) uma pessoa ativa na comunidade, que compartilha conhecimento dentro e fora da empresa através de eventos, artigos, mentorias, iniciativas voluntárias, projetos open source, etc.
  

Etapas do processo seletivo:

• Aplicação - Envio da inscrição;
• Mindsight – Teste de estilo de trabalho;
• Talent Acquisition - Entrevista por competência com o time de recrutamento;
• Desafio Técnico – Teste de avaliação de habilidades técnicas;
  
• Entrevista Final - Entrevista técnica e final com a coordenação para alinhamento;
• Offer - Fase de conclusão do processo seletivo, com a apresentação da proposta de trabalho.

Obs: Podem ter etapas complementares e/ou alterações, de acordo com a necessidade do processo.

AE Studio is a development, data science, and design studio that works closely with founders and executives to create custom software and machine learning solutions.

We build products, platforms, and internal ventures that increase agency for all conscious beings. We combine world-class software engineering, AI expertise, and product design to ship ambitious projects that matter.

We’re looking for a Full-Stack Developer who bridges modern web engineering with practical AI; someone who can design, build, and ship production-ready, AI-powered applications while maintaining the standards of a top-tier software developer.

What You’ll Do

• Design and ship end-to-end applications from prototype to production across frontend, backend, and cloud.
• Build clean, scalable APIs and services and integrate AI models where they create real value.
• Create AI pipelines (data ingestion, preprocessing, embeddings, retrieval, orchestration) that are reliable and maintainable.
• Engineer prompting strategies and guardrails for real-world performance (latency, cost, accuracy), not just demo hype.
• Integrate AI features into full-stack apps with robust APIs, frontend UX, and CI/CD pipelines.
• Collaborate with designers, PMs, and engineers to deliver polished product experiences.
• Continuously evaluate new AI tools/models for performance, cost, and fit.
• Write production-grade, testable, maintainable code in TypeScript/JavaScript and Python (and other languages as needed).
  
  

What We’re Looking For

• 7+ years of professional software engineering experience.
• Proven track record shipping production applications (links to live products welcome).
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic), embeddings, vector databases, and orchestration frameworks.
• Strong command of modern web stacks (e.g., React/Next.js, Node.js/Nest/Fastify, Python/FastAPI) and cloud infrastructure.
• Solid grasp of architecture, scalability, performance, and security.
• A bias toward shipping with best practices (testing, code reviews, monitoring/observability).
• Clear communication, self-management, and comfort in a collaborative remote environment.
• Comfortable picking up new languages and frameworks, leveraging modern AI dev tools to move faster.
  
  

What Sets You Apart

• Experience fine-tuning models or training custom models on domain-specific data.
• Contributions to open-source AI or developer tooling.
• Mature approach to prompt engineering and evaluation (beyond trial-and-error).
• Background in data engineering or MLOps.
• Passion for AI alignment, agency-increasing technologies, and ethical AI development.
  
  

If you can write prompts that work today and code that still works in two years, we want to talk to you.

Salary range from $115k/year to $185k/year (if you're based in LA). Not in the range? That's fine, you can still apply and our team may fit you in a more senior position that we're not actively hiring for right now, since we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across Patient Experience and Commercial Operations functions. This role is focused on improving how patients navigate testing and billing while enabling operational teams to efficiently progress cases from order to completion. You will play a crucial part in supporting initiatives to reduce friction, improve patient trust, and increase operational efficiency, ultimately driving better conversion, collections, and experience.

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with domain leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across the associated functions. The role has direct ownership of high-impact initiatives that deeply influence organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the Patient Experience + Commercial Operations pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., stuck cases, fragmented patient communication, support inefficiencies, billing friction) into clear product direction and measurable outcomes
• Own the line between 'what the business needs' and 'what gets built' end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, case completion turnaround)
• Influence Patient Experience and Commercial Operations stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Patient Experience and/or Commercial Operations
• Strong understanding of patient journeys, support channels (e.g., chat, voice, call centers), and operational workflows that drive conversion and test completion
• Familiarity with key domain-relevant tooling (e.g., patient portals, support platforms) and associated data
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems, including patient, provider, payer, claims, billing, and clinical trial data
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., case completion turnaround time, patient satisfaction, cost-to-serve)
• Reliable, high-quality data foundations connect patient, provider, clinical, operational, and billing/financial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function's roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals

Sobre a Vitta

Já se imaginou trabalhando em uma empresa que tem como missão transformar a vida das pessoas? 

Se você é guerreiro, então essa é a sua chance de entrar em um exército que está crescendo e pronto para mudar a saúde do Brasil!

Nós da Vitta somos responsáveis pela vertical de saúde e seguros do Grupo Stone Co. empresa listada em Nasdaq, em NYC. Somos apaixonados por pessoas e inovação. Temos um chamado! Se você quer ter um impacto significativo na saúde do Brasil e ao mesmo tempo aprender muito e fazer parte de um time de altíssimo nível, queremos te conhecer!

Nossa cultura:

Por aqui, vivemos nossa cultura no dia a dia, guiados por esses 5 pilares:

⚡Own It: Ter espírito de dono te faz conquistar a liberdade. Valorizamos a autonomia e a proatividade, somos responsáveis pelo o que entregamos e queremos sempre evoluir o nosso negócio. 

🎢Live the Ride: Faça. Feito é melhor que perfeito. Aprendemos com os erros e encaramos desafios como oportunidades de aprendizado.  

🎤No Bullshit: Agir com simplicidade. Somos pessoas práticas, sinceras e gostamos de feedbacks. Sabemos que às vezes vamos errar e contamos com essa transparência para evoluirmos. 

🤝Team Play: Se quer ir rápido, vá sozinho(a). Se quer ir longe, trabalhe em equipe. É sempre possível aprender com as outras pessoas e a colaboração é a chave do sucesso. 

💚The Reason: O cliente não tem razão, ele é a razão. Nos motivamos a enxergar o impacto do nosso trabalho na vida do cliente, é vendo que melhoramos a vida dele que sabemos que fizemos uma boa entrega. 

Como é ser uma pessoa Cientista de Dados Sênior na Vitta:

Estamos em busca de um(a) Cientista de Dados Sênior com perfil consultivo e forte capacidade de liderança técnica para atuar na condução de projetos estratégicos de dados. Essa pessoa será responsável por traduzir problemas de negócio em soluções analíticas, liderar iniciativas ponta a ponta e atuar como ponte entre áreas técnicas e stakeholders. Mais do que construir modelos, esperamos alguém que consiga estruturar problemas, influenciar decisões e garantir que os projetos gerem impacto real no negócio.

Responsabilidades:

• Atuar de forma consultiva junto às áreas de negócio, entendendo dores e propondo soluções baseadas em dados;
• Liderar projetos de ciência de dados de ponta a ponta (da definição do problema à entrega em produção);
• Traduzir problemas de negócio em abordagens analíticas (modelos preditivos, segmentações, otimizações, etc.);
• Comunicar resultados e insights de forma clara para stakeholders técnicos e não técnicos;
• Garantir qualidade, reprodutibilidade e governança dos modelos desenvolvidos;
• Comunique pontos técnicos, decisões e trade-offs para pares e stakeholders;
  

O que esperamos de você:

• Experiência sólida em Ciência de Dados aplicada a problemas reais de negócio;
• Forte habilidade de comunicação e storytelling com dados;
• Experiência liderando projetos e interagindo diretamente com stakeholders;
• Domínio de Python e bibliotecas de dados (Pandas, Scikit-learn, etc.);
• Conhecimento em SQL e manipulação de grandes volumes de dados;
• Experiência com deploy de modelos (MLOps é um diferencial);
• Capacidade de estruturar problemas ambíguos e propor soluções pragmáticas;
• Conhecimento em IAs generativas;
  

O que aumenta as suas chances:

• Experiência em ambientes orientados a produto ou consultoria interna;
• Conhecimento em arquitetura de dados moderna (ex: lakehouse);
• Conhecimentos em ferramentas AWS;
• Vivência em priorização de backlog e frameworks de decisão;
• Conhecimento em experimentação (A/B testing);

Nossos benefícios:

🩺 Plano de Saúde e Odontológico

🏥 Hospital Digital: contamos com uma equipe médica multidisciplinar, terapeutas e um time de saúde disponível 24 horas por dia, 7 dias por semana, de forma rápida e prática

🥗 Vale Refeição e/ou Vale Alimentação - Flash

💪 Gympass/Wellhub

👶 Auxílio Creche - para crianças até  5 anos e 11 meses

🐶 Auxílio Pet

🌴 Férias&CO

🌼 DayOff de aniversário e DayOff de aniversário do filho de até 11 anos

💙 Seguro de Vida

🚗Vale Transporte (exclusivo para vagas presenciais)

Etapas do Processo Seletivo:

✍Inscrição: Aqui você começa a sua jornada conosco. Fique tranquilo(a), nosso time analisará as informações do seu perfil e entrará em contato em breve. Boa sorte!

📞Entrevistas com o time de People: Este é o momento de nos conhecermos! Você terá um papo inicial com nosso time de recrutamento, com o objetivo de conhecer nossa cultura, estrutura e o desafio que está sendo proposto. 

🎯Avaliação Técnica: Nesta etapa vamos nos aprofundar nas suas hard skills! Geralmente essa avaliação é composta por dois papos ou um papo mais o desafio, com o objetivo de avaliar habilidades e competências técnicas específicas para a vaga. Além de te apresentar possíveis pares e liderança.

✅Check de Cultura: Nossa cultura é muito importante e está sempre presente no dia a dia! Aqui, você terá um papo com uma das nossas pessoas guardiãs da cultura, com o objetivo de nos conhecer e garantir que nossas crenças, nosso jeito de pensar e nossa visão de futuro estão alinhadas com o que você acredita e busca vivenciar.

🏁Feedback: Uma de nossas forças é a franqueza. Por isso, independente do resultado, iremos compartilhá-lo com você e alinhar os próximos passos.

E aí? Curtiu? Então, não deixa de se inscrever e #VemSerVitta 💙🚀

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across the go-to-market and operational teams embedded within Natera’s core business units (i.e., Oncology, Women’s Health, Organ Health), including Sales, Marketing, and Medical stakeholders. 

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with ‘S&M + GM’ leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across Sales, Marketing, Medical, and related functions.

This role sits at the intersection of business impact and technical depth, with deep visibility into commercial performance and executive decision-making. You will have direct ownership of high-impact initiatives fueling overall organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the S&M + GM pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., churn risk, campaign performance, clinical profile segmentation, next-best-action orchestration) into clear product direction and measurable outcomes
• Own the line between ‘what the business needs’ and ‘what gets built’ end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, forecasting accuracy)
• Influence across Sales, Marketing, Medical, and GM stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Sales, Marketing, Field Medical, and/or related commercial/GTM functions 
• Strong understanding of sales funnel, marketing funnel, medical affairs funnel, and related funnels to relate product ideas to the overall opportunity landscape
• Familiarity with key domain-relevant tooling (e.g., Salesforce) and associated data 
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., increased sales efficiency, better campaign performance)
• Reliable, high-quality data foundations connect patient, clinical, financial, and commercial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function’s roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals
  
  

#LI-DNI

About Incode

Incode is the leading provider of world-class identity solutions that is reinventing the way humans authenticate and verify their identities online to power a world of digital trust.

Through our revolutionary identity solutions, we are unleashing the business potential of universal industries including finance, government, retail, hospitality, gaming, and more, by reducing fraud and transforming human interactions with data, products, and services.

We're in the process of rapidly scaling our diverse global team and we're looking for entrepreneurial individuals and leaders who are curious, driven, and excited by ownership to join a Unicorn-status scale-up!

Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security.

Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we're scaling fast — and we're looking for data professionals passionate about investigating data quality problems and building the systems that keep world-class ML models reliable.

The Impact You'll Make

As a Data Analyst on the ID Document Intelligence team, you'll investigate data quality issues, perform root cause analysis, and build the pipelines and automated checks that keep Incode's machine learning ecosystem reliable. You'll ensure that data flows efficiently and accurately through every stage of model training, labeling, and performance tracking.

Your work will be essential to maintaining the scalability, quality, and precision of Incode's document intelligence systems used by millions worldwide.

What You'll Own & Drive

• Root Cause Investigation — Independently investigate data quality issues end-to-end. When a model metric drops or data looks wrong, you own the investigation: forming hypotheses, querying across data sources, and delivering a clear, evidence-backed answer.
• Automated Data Pipelines — Design, build, and maintain pipelines for collection, labeling, validation, and metric computation that support ML training and evaluation.
• Data & Labeling Quality Standards — Establish and monitor consistency checks, accuracy audits, and root-cause analysis when issues impact model outcomes.
• Model Evaluation Metrics — Define, implement, and automate evaluation metrics and reporting that reflect real-world product use cases and business goals.
• Performance Tracking Systems — Build scalable dashboards and monitoring to enable fast, data-driven decisions across teams.
• Workflow Orchestration — Develop and operate reliable orchestration (Airflow, Prefect, or similar) to schedule, observe, and troubleshoot end-to-end pipelines.
• Clean, Maintainable Code — Write SQL and Python to efficiently investigate problems — querying databases, calling internal APIs, and processing data across multiple sources.
• Cross-Functional Partnership — Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact, unblock execution, and continuously improve internal tooling for analysis and evaluation.

The Qualities That Set You Apart

• Investigative mindset — You don't stop at the symptom. You chase data anomalies until you find the root cause, and you bring receipts.
• Statistical intuition — You can tell the difference between a meaningful metric shift and noise, and you know how to prove it.
• Builder's bias — You'd rather automate a check than run it manually for the third time.
• Proactive ownership — You spot problems before anyone flags them, and you drive them to resolution without waiting for permission.
• Clear communicator — You translate messy data into crisp answers that ML engineers, PMs, and leadership can act on.

Your Background

• 3+ years of experience as a Data Analyst or in a similar data infrastructure role.
• Strong SQL and Python skills for data investigation and root cause analysis.
• Hands-on experience with AWS Redshift or a similar columnar/cloud database (BigQuery, Snowflake, etc.).
• Solid statistical foundation — you can reason about rates, distributions, significance, and sampling bias.
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
• Proven experience in data quality management, data preparation, or ML data pipelines.
• A proactive mindset toward identifying problems.
• Strong collaboration and problem-solving skills.
• Background in mathematics, physics, or engineering.

Preferred Experience

• Familiarity with big data technologies or data infrastructure optimization.
• Experience with labeling workflows or ML data preparation pipelines.
• Exposure to AWS or other cloud-based data solutions.
• Interest in machine learning operations (MLOps) and scalable ML systems.

Why Incode?

• Mission with Meaning — Build systems that enable ethical, seamless identity verification for millions.
• Rocket-Ship Growth — Join a company scaling globally with AI at its core.
• Elite Team & Technology — Collaborate with top engineers and data scientists redefining document intelligence.
• Ownership & Autonomy — Operate with end-to-end responsibility for impactful data pipelines.
• Global Impact — Your work will power real-world AI experiences trusted by major enterprises.

Power a world of trust.

REJOINS L'ÉQUIPE PRICE & PROMOTION RECOMMENDATION ENGINE

Au sein du domaine Customer Relationship, notre équipe développe et industrialise des solutions d'IA dédiées à la stratégie de prix de Decathlon. Nous concevons des moteurs de recommandation qui calculent le prix optimal de chaque produit en analysant l'élasticité-prix, les données de comportement d'achat des clients et les indicateurs de performance du marché.

L'objectif est d'intégrer ces modèles dans la stratégie Decathlon pour garantir une cohérence entre l'offre et les attentes des utilisateurs.

Pour cela, nous collaborons dans une organisation agile composée de Product Managers, Data Scientists, Data Engineers, Machine Learning Engineers et Data Analysts.

MACHINE LEARNING ENGINEER - ALTERNANCE

Dans le cadre de l’ouverture d’un poste en interne, nous recrutons un.e Machine Learning Engineer en contrat d’apprentissage/stage, basé.e à Paris.

Déployer les moteurs de recommandation en production est un enjeu clé pour fournir des recommandations précises, fiables et robustes. Ton rôle sera de garantir que nos modèles de prix et de promotions s'adaptent en continu aux besoins des sportifs. Tu travailleras sur l'industrialisation du cycle de vie des modèles pour assurer une expérience fluide et sans friction sur tous nos canaux (digital et magasins) via les bonnes pratiques MLOps.

Cela inclut différentes problématiques telles que le monitoring de la qualité et de l’évolution des données (data drift), la surveillance des performances du modèle, l’orchestration des prédictions, la stratégie de ré-entraînement du modèle… Une bonne maîtrise de ces sujets est essentielle pour pérenniser la valeur créée par le modèle.

TES MISSIONS

Parfaitement intégré(e) à l'équipe en place, ton rôle sera de participer à chaque étape des projets, du cadrage à la solution finale, et de découvrir les bonnes pratiques de développement. Tu contribueras à la mise à l'échelle des solutions data et d'apprentissage automatique d'un POC à un produit entièrement déployé.

Tu commenceras par une période de formation avant de travailler sur les projets de l’équipe sous la responsabilité d'un référent Data expérimenté.

• Tu contribueras aux projets existants comme tous les membres de l’équipe.
• Tu effectueras une revue de l'état de l'art scientifique sur le domaine (ex. orchestration d’agents IA).
• Tu testeras ces nouvelles méthodes sur un cas d'usage réel étudié en ce moment dans notre équipe en appliquant les meilleurs standards Data.
• Tu implémenteras ces nouvelles fonctionnalités dans nos pipelines et mettre en production ton modèle en utilisant des principes d'ingénierie de qualité.
• Tu communiqueras efficacement l'analyse et les résultats par le biais de visualisations, de documents et de présentations aux parties prenantes techniques et business.

Tu auras l’opportunité de :

• Mettre à contribution tes compétences acquises lors de ta formation pour t'adapter rapidement à la stack technique Decathlon : Python - Git - SQL - Spark - Visualisation.
• Développer et documenter tes modèles et analyses (data sourcing, hypothèses et méthodes) dans une logique Agile en respectant les standards appliqués au sein des équipes Decathlon.
• Expliquer l’utilisation de la data et sa valeur ajoutée.

TON ENVIRONNEMENT TECHNIQUE

• Data & ML : Python, Scikit-Learn, Pytorch, Pyspark, SQL
• Cloud & Infra : AWS, GCP, Databricks
• MLOps : MLFlow (tracking), Airflow (orchestration), Evidently (monitoring).
• DevOps & Tools : GitHub Actions, Git, Docker, API
• Méthodologie : Agile

CE DONT TU AS BESOIN POUR RÉUSSIR

• Une première expérience significative (projets universitaire, stage ou alternance) dans un environnement technique similaire.
• Une appétence forte pour le travail en équipe et une culture du partage.
• Un intérêt pour l’impact du sport sur le développement personnel et collectif.
• L’envie de rejoindre une entreprise engagée dans le Tech4Good et l’innovation responsable.

POURQUOI NOUS REJOINDRE ?

Chez Decathlon, nous mettons un point d’honneur à offrir un cadre de travail épanouissant et motivant.

🚀 Un environnement de travail stimulant : entreprise certifiée Great Place to Work et Happy Trainees.
💰 Des avantages attractifs (après 3 mois d’ancienneté) :

• Primes mensuelles, intéressement, actionnariat
• Avantages CSE
• 25% de réduction sur nos produits
• Prise en charge de ta CVEC
• Remboursement de 50% du titre de transport & aide à la mobilité urbaine
  🎯 Un accompagnement sur mesure : coaching, formations internes et externes, partage de connaissances.
  ⚡ Une culture du sport et du test produit : deviens ambassadeur.trice de nos innovations et rejoins nos équipes sportives internes !

FAQ – TOUTES TES QUESTIONS

Comment préparer ma candidature et comment se déroule le processus de recrutement ?

1️⃣ Lis bien l’offre et mets en avant tes expériences et compétences les plus pertinentes.
2️⃣ Personnalise ton CV pour te démarquer.
3️⃣ Après candidature, tu recevras une réponse sous quatre semaines. Si tu es sélectionné.e, tu passeras au moins deux entretiens avec ton futur leader et un.e référent.e métier.

Je ne connais pas le secteur du sport, ai-je ma place chez Decathlon ?

Bien sûr ! Nous recherchons avant tout des personnes passionnées et motivées, que ce soit dans leur domaine d’expertise ou par le sport en général.

Être étudiant chez Decathlon, c’est quoi ?

C’est bien plus qu’une simple alternance ou un stage ! C’est façonner ton avenir professionnel en contribuant à des projets concrets qui ont du sens pour toi, tout en étant accompagné et soutenu à chaque étape.

🎯 Notre ambition ? T’offrir une expérience enrichissante pour te préparer à ton futur métier et, pourquoi pas, t’accueillir en CDI à l’issue de ton alternance. D’ailleurs, plus de 50% de nos étudiants rejoignent définitivement l’aventure Decathlon ! 🚀

The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices.

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
• Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
• Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning, prompt engineering, and model adaptation.
• Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives, architects, and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organization’s AI strategy and technical direction.

Required Qualifications

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research, open-source projects, or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.

Job Title:

The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices. 

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
• Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
• Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning, prompt engineering, and model adaptation.
• Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives, architects, and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organization’s AI strategy and technical direction.

Required Qualifications

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research, open-source projects, or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

As Senior Data Engineer – Internal Platform, you will build and own the data infrastructure that powers Parloa's internal AI transformation. Today, business-critical data lives across dozens of disconnected tools with no unified way to access it — you'll change that by creating a single, self-serve access layer that gives AI agents and teams the business context they need to operate. Working closely with the AI Transformation Team and stakeholders across the non-engineering organization, you'll also define the KPIs and dashboards leadership uses to track AI adoption and impact.

Areas of ownership:

• Data Platform Infrastructure: Own the Internal-facing Databricks workspace end-to-end: configuration, compute, access controls, and cost management.
• Ingestion Pipelines: Build and maintain Airbyte pipelines that pull data from Salesforce, Gong, HRIS, finance systems, and other tools on automated schedules.
• Data Modeling & Transformation: Implement the architecture that turns raw data into clean, trusted, analysis-ready datasets.
• AI Data Enablement: Partner with the AI Transformation Team to ensure AI agents and LLM workflows get the right data in the right format.
• AI Adoption Measurement: Define and build the KPIs and dashboards that track AI usage, proficiency, and business impact across the company.
• Data Governance & Compliance: Own data classification, access policies, GDPR/DPA compliance, and pipeline monitoring.

Who you are:

• Experience designing data layers that power AI/LLM-based applications and agentic workflows.
• Proficiency in Python, SQL, ETL/ELT tools, and MLOps.
• Knowledge of dimensional modeling and modern data warehouse technologies.
• Ability to comprehend and execute on complex requirements and resolve performance issues.
• Ability to articulate complex technical concepts to non-engineering audiences, making data architecture decisions and trade-offs understandable for leadership and cross-functional stakeholders.
• Passion for staying updated and driving innovation in data engineering.
• Ability to define and instrument Al adoption KPls: usage tracking, proficiency distribution, and business impact metrics.
• Understanding of how Al tools consume data – context windows, retrieval patterns, embedding pipelines – and how to optimise data access for.

Our recruiting process:

Talent Acquisition → Hiring Manager → Technical Interview(s) → Bar Raiser

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale and want your work to matter in real, everyday moments, this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

Applicants must be authorized to work for any employer in the U.S. without sponsorship. We are unable to provide sponsorship for work visas of any kind at the time of hire, or at any point during employment. This includes, but is not limited to: F1-OPT, F1-CPT, H-1B, TN, J-1, etc.

Location: Live in or able to relocate to San Francisco / San Jose area

Your Role:

Tenable is not only building great products and carving out a completely new category, but we are also building a world-class engineering culture committed to hiring the very best.

We are looking for a Senior Software Engineer to join a founding initiative within our engineering organization. In this role, you will help design and implement the Agentic AI Platform, the orchestration layer and nervous system that enables autonomous agents to reason, plan, and execute complex security workflows across our Exposure Management ecosystem.

This is a hands-on engineering role with broad impact. You will not just be "using" LLMs; you will be building the distributed systems, state machines, and tooling that transform generative models into reliable, enterprise-grade agents. 

While you will work from home the majority of your time, there may be an expectation to gather for in-person meetings on occasion. 

Your Opportunity:

• Build the Agentic Backbone: Architect and implement the backend services that power multi-agent workflows. You will build systems that allow AI agents to decompose complex user requests, manage state, and execute tasks across distributed microservices.
• Orchestration & Workflow Automation: Design scalable workflow engines and "human-in-the-loop" systems. You will enable agents to perform long-running investigations and remediation tasks, balancing autonomy with control.
• Bridge AI & Enterprise Infrastructure: Create the integration layer between modern Python-based AI frameworks and Tenable’s robust JVM-based microservices architecture.
• Reliability & Guardrails: Implement verification layers, citations, and security guardrails to ensure agents operate deterministically and safely. You will treat "prompts" as code and model outputs as untrusted input that requires validation.
• Tooling & RAG: Build advanced Retrieval-Augmented Generation (RAG) pipelines and "Tool Use" capabilities, allowing agents to query databases, call internal APIs, and synthesize data from disparate sources.
• Lead Technical Direction: Collaborate with researchers and product leads to define the roadmap for AI orchestration. Champion best practices for MLOps, agent evaluation, and system observability.

What You’ll Need:

• B.S. or M.S. in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 5+ years of software engineering experience (7+ for Staff level), with a strong background in building backend systems, APIs, and platforms.
• Agentic AI Expertise: Hands-on experience building AI agents and autonomous workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Pydantic AI.
• Location: Live in or able to relocate to San Francisco / San Jose area
• Polyglot Proficiency: Strong programming skills in Python (essential for AI/ML ecosystems) with experience in, or a willingness to work with, JVM-based languages (Java, Kotlin, or Scala) for high-scale platform components.
• Distributed Systems: Experience designing event-driven architectures, managing concurrency, and building fault-tolerant services (e.g., using Kafka, gRPC, REST).
• Data Fluency: Proficiency with Relational Databases (PostgreSQL) and experience with Vector Databases (e.g., Pinecone, Weaviate, Milvus) or search engines (Elasticsearch).
• Builder Mindset: A self-starter who thrives in ambiguity and is passionate about taking AI from "prototype" to "production-grade."

And Ideally:

• LLM Ops & Evaluation: Experience designing frameworks to evaluate agent performance (accuracy, latency, cost) and implementing CI/CD for AI workflows.
• Cloud Native: Experience deploying and scaling services in AWS using Docker and Kubernetes.
• Graph & Search: Familiarity with Knowledge Graphs or advanced search algorithms to improve agent reasoning.
• Security Context: Understanding of cybersecurity concepts (vulnerability management, cloud security) is a plus, but not required if you are a strong systems engineer.

#LI-LP1

We're building a new product team in India to help shape how customers build, deploy, and operate AI applications on MongoDB. This is an early hire on a growing team—you'll join while the team is still taking shape, with the opportunity to have real impact from the start.

You'll report to a Director of Product Management based in Europe, working async-first with partners across India, EMEA, and North America. The engineering team in India is being built in parallel, so you'll be working closely with engineers from the early days of the team.

We are looking to speak to candidates based in Gurugram for our hybrid working model.

What you'll own

You'll be the end-to-end owner for a core area of our AI application platform—from discovery and vision through roadmap, delivery, and iteration. This is a senior individual contributor role where you lead through ownership, expertise, and cross-functional influence.

Day to day, that means:

• Defining product strategy and roadmap for your area, aligned with MongoDB's broader AI strategy and business goals
• Talking to customers — from AI-native startups to large enterprises — to understand how they build and deploy AI applications, where they struggle, and what MongoDB should do about it
• Writing clear product narratives, memos, and specs that align stakeholders, clarify trade-offs, to guide conversations with engineering, design, product marketing, etc
• Partnering with cross-functional stakeholders—including Engineering, Design, Product Marketing, Partners, Sales, and Developer Relations—to scope, prioritize, and ship, balancing experimentation with reliability and scale, and driving positioning, launches, and enablement
• Identifying new opportunities autonomously—spotting gaps, shaping problem spaces, researching industry trends and running discovery sessions with customers
• Define and own clear success metrics for your area and use them to prioritize, make trade-offs and communicate impact

You'll develop deep expertise in how companies build AI applications — including agentic workflows, retrieval and memory, evaluation, observability, and deployment patterns.

How we work

• Async-first. Documentation and written communication are how decisions travel across time zones
• Sync when it makes sense. When we need to discuss something live, we hop on a call to unbundle issues together
• In-person when it matters. The team gets together periodically for planning, relationship-building, and the kind of work that's better done face to face

What you'll bring

• 5+ years in product management (or equivalent) building platforms, infrastructure, or developer-facing products — ideally in cloud, data, or AI
• Proven end-to-end ownership of a product area: from framing the problem and vision through roadmap, execution, launch, and iteration
• Customer obsession: you're comfortable running discovery calls, digging into workflows, and turning messy feedback into clear product decisions
• Strong written and live communication: clear docs, productive meetings, confident stakeholder presentations. This matters more in an async, distributed team — writing is how you lead
• Technical depth sufficient to collaborate with senior engineers on distributed systems, cloud services, and AI/ML tooling, and to ask good questions when something is unclear
• Curiosity about AI: you follow how companies are building AI applications — agents, orchestration frameworks, RAG, fine-tuning, or other emerging patterns
• Comfort with ambiguity: you help define the problem, the success metrics, and the path forward. In an early-stage team, this is the job

Bonus points

• Experience building developer tools, AI platforms, or MLOps/LLMOps products.
• Engineering background or deep experience partnering with engineering on technical products.
• Experience with enterprise customers on mission-critical workloads.
• Comfort using AI tools (e.g., Claude, Gemini, Figma Make) to move faster and amplify impact.

How we'll measure success (30/60/90 days)

We need someone who can onboard quickly and start driving impact early.

In your first 30 days, you will:

• Ramp up on MongoDB products, AI application patterns, and how our teams work
• Shadow customer calls and internal forums to learn current strategy, open questions, and key stakeholders
• Produce a clear written overview of your product area: current state, key bets, and known gaps

By 60 days, you will:

• Take ownership of a set of customer relationships and run your own discovery conversations each week
• Own and socialize an initial strategy and roadmap proposal for your area, with clear problem statements and success metrics
• Partner with engineering and design to shape and drive at least one scoped initiative into execution

By 90 days, you will:

• Be the go-to owner for your product area, driving prioritization and day-to-day decision-making across functions
• Lead customer- and data-informed iterations on what you’ve shipped, adjusting the roadmap based on what you’re learning
• Contribute to the broader AI application platform strategy with perspectives from your domain, customers, and the field

Why this role

MongoDB is one of the most widely adopted database platforms in the world, used by tens of thousands of customers — including much of the Fortune 100 and a fast-growing set of AI-native startups. Our cloud platform, Atlas, runs across AWS, Google Cloud, and Azure.

This role puts you at the center of how MongoDB powers AI applications at scale. You’ll own a critical slice of that story, from strategy through delivery and adoption.

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

The Trade Desk is a global technology company with a mission to create a better, more open internet for everyone through principled, intelligent advertising. Handling over 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, ownership, empathy, and collaboration. We value the unique experiences and perspectives that each person brings to The Trade Desk, and we are committed to fostering inclusive spaces where everyone can bring their authentic selves to work every day.

Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally- connected team where your contributions will make a meaningful difference in building a better media ecosystem? Come and see why Fortune magazine consistently ranks The Trade Desk among the best small- to medium-sized workplaces globally.

What we do  

Our Software Engineers are end-to-end owners who have the opportunity to participate in many aspects of designing, building, and delivering data-focused products for our stakeholders.  

At The Trade Desk, we believe in building the back-end infrastructure of our platform with a focus on quality at scale. This means whether we are building parts of our client-facing applications, internal custom solutions for our own team members, or model pipelines for bidding optimizations, we are making sure that we have infrastructure, development, and tools to do it right and efficiently.  

Our system performs all day, every day serving global traffic. We build a distributed system in a highly collaborative environment, utilizing a broad range of technologies. Our back-end developers work on finding solutions to algorithmic, optimization and scale challenges in everything we do.

About the role:

The Trade Desk Software Engineers are best described as end-to-end owners.

• You will participate actively in all aspects of product strategy – from designing, building, and delivering products for our clients.
• We have dozens of individual, mission-focused teams working across a wide spectrum of technological challenges.
• You will have the opportunity, depending on your interests and aptitude, to lead engineers that focus on building large-scale distributed systems coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, machine learning, advanced visualizations, and interactive user interfaces – to name a few.
• Software Engineers contribute to more than our product – they help build up our team. Through a combination of mentoring and technical leadership of local teams, you will make others better and raise the bar for those around you.

We are a global team with different backgrounds, experiences and perspectives. To complement this team, you will welcome ideas that are different from your own and be well-versed in building from common ground to value, seek out, and foster invisible and visible dimensions of diversity. 

Who you are: 

Our culture is much deeper than just having fun together (though, we do that well too...). We take pride in our engineers being trust-builders, generous givers, scrappy problem solvers, and gritty pursuers of excellence. You do not have to meet all the requirements below, but we believe that people who meet most of them will have a higher likelihood of succeeding in this role: 

• The ideal candidate will have 2 to 5 years of impactful hands-on software engineering experience
• You are a strong communicator. You’re able to collaborate cross functionally with data scientists and root cause pain points in their workflow.
• You have a passion for improving the efficiency of others. The work you will do in Machine Learning Operations will have a big impact on both the data scientists and the data engineers in our organization.
• Experience building large scale data pipelines with spark is a plus.
• Experience building machine learning models is a plus.
• You have a Bachelor’s/Master’s level degree in a computer-science or relevant engineering related field or equivalent experience. Not everyone has the same level of access to opportunities. What is most important to us is what and how you can contribute, which is why our consideration is not limited by the level of education you have.
• You think beyond just the task at hand to deeply understand the 'why' behind what you & your team are doing.
• You are a driver. You will own technical milestones and projects in a ground-breaking and fast-paced environment, driving them from inception till completion. This includes task planning, individual code contribution, and code reviews.
• You understand engineering fundamentals. At our scale, many off-the-shelf techniques and existing technologies (open source and enterprise) simply don't work.
• You are able to work from first principles to evaluate solutions and adapt them to a unique environment.
• You are a broadly skilled engineer, accustomed to developing web services.
• You have experience building always-on systems, working across a variety of technologies and service layers.
• You have a product-focused mindset.
• You have the passion and ability to contribute to the process of discovering what will delight our clients and push forward one of the world’s largest and most influential industries toward a vision of openness, transparency, and evidence-based decision-making.
• You work with confidence and without ego. Our engineers have deep knowledge and exercise a high degree of leadership in their daily work.
• You have strongly-held, defensible ideas, and advocate for what you believe is right.
• You are also adept at identifying and evaluating trade-offs, willing to be proven wrong, and quick to walk through fire to support your fellow teammates.
• You value, seek out, and foster diversity.

Variety of technical opportunity is one of the best things about working at The Trade Desk as a software engineer which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We don't need engineers who know all the answers; we need engineers who can invent the answers no one has thought of yet, to the questions yet to be asked.  

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#LI-AD1

We are seeking a high-impact Staff Data Scientist to play a leading role on our data needs to bridge the gap between advanced research and production-grade ML systems. You will be a key technical leader and partner to our Research Scientists, driving the evolution of our AI algorithms through rigorous data science methodologies, strategic data curation, and cross-functional leadership.

Job Responsibilities:

• Vision & Cross-Functional Leadership: Engage with cross-functional teams (Product, Research, Engineering, and Process Engineering) and help guide the overarching vision for data analysis, curation, and annotation to improve our AI models. Drive the definition of algorithm and data requirements necessary to deliver on end-point objectives.
• Data Campaigns and Annotation Strategy: Introduce best practices and efficient processes to enable multiple, large-scale annotation campaigns for continuous AI product improvements. Spearhead the strategic design of data campaigns needed to advance AI algorithms.
• Advanced Data Curation & Management: Develop comprehensive data curation strategies for improvements to AI models. Partner with MLOps to architect data management systems for algorithm training and performance validation, and establish data dashboards and monitoring reports.
• Performance Evaluation and Statistical Analysis: Establish frameworks and develop tools to rigorously evaluate the strengths and weaknesses of model iterations across patient populations. Design and oversee data analyses using statistical techniques to illuminate the performance of our AI algorithms.

Required Qualifications:  

• Education: Masters or PhD Degree in Engineering, Computer Science, Statistics, Data Science or related degree.
• Work Experience: 7+ years (or 5+ with PhD) of proven track record in Data Science, Machine Learning, Computer Vision, or Image Analysis in industry. Have a wealth of experience from working on complex, real-world AI problems in medical imaging or computer vision requiring careful consideration of data needs.
• Software: Proficient in Python, including statistical and machine learning packages (e.g. scipy, sklearn, statsmodels, seaborn) with a commitment to writing clean, reproducible and scalable code. Familiarity with image and 3D processing tools like VTK and ITK, and visualization tools like 3DSlicer and MITK, a plus.
• Statistics: Understanding of standard statistical techniques and ability to apply appropriate statistical methods to a range of data structures; experience with medical imaging data a plus.
• Data Management: Experience working with data lakes, SQL/No SQL Databases, AWS Cloud Storage, Tableau dashboards.
• AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong experience working with medical imaging data (CT and vascular imaging) is highly preferred.
• (Preferred) Proficiency in Agentic AI Tools: Experience integrating generative AI and agentic tools into daily workflows to act as a force multiplier—accelerating coding, prototyping, and complex data analysis—while demonstrating the critical judgment required to rigorously evaluate AI outputs for accuracy.
• Communication: Excellent written and verbal communication. Detail orientated but able to describe complex topics in a manner that is digestible to a broad audience. Ability to distill complex analyses into interpretable and actionable findings.
• Commitment: Committed to the success of the team and successful completion of project - 75% confidence / 100% committed.
• Influence without Authority: Able to build trust and obtain cross-functional alignment across departments.

A reasonable estimate of the base salary compensation range is $220,000 to $280,000, bonus, and equity. #LI-IB1 #LI-Hybrid

Who We Are

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials.  Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes.

Where You Fit 

Our Intern/Co-op program is designed to give you a real-world view of what it's like to be a Machine Learning Engineer at PathAI. You will be embedded directly into our AI product and ML Core teams, working on active projects that have a direct impact on our technical roadmap and business goals.

You will collaborate with a cross-functional team of scientists, engineers, and product managers to translate clinical needs into scalable ML solutions. This is your chance to contribute to meaningful work that directly relates to patient outcomes.

Timeline: This opportunity is for Fall 2026. We are looking for interns/co-ops who can commit to 3-6 months at PathAI (4-6 months preferred).

Location: We have offices in Boston, MA and New York, NY and would prefer interns/co-ops who can work from one of those locations—however, we will also consider remote candidates (US based only).

What You’ll Do

• Contribute to the design, development, and evaluation of machine learning models for our AI products, AI services and core ML models.
• Work on subprojects derived from our ongoing ML product roadmap, focusing on areas like model improvements with novel techniques.
• Partner with our MLOps and platform teams to help build and improve our ML pipelines.
• Participate in experimental design, analysis, and team knowledge-sharing initiatives like design reviews, technical forums and journal clubs.

What You Bring 

• Currently pursuing a M.S., or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering with a focus on Computer Vision and Machine Learning.
• Strong programming skills in Python and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow).
• A solid grasp of the fundamentals of machine learning and/or computer vision.
• Excellent communication skills and a desire to work in a highly collaborative, cross-functional environment.
• A passion for our mission to improve patient outcomes.
• [Nice-to-have] Any high impact contributions through any AI/ML publications, open-source projects and any AI based products.

We are looking for team players who are passionate about what they do and are willing to tackle any task to contribute to our goals. You could be exactly who we are looking for!

We Want To Hear From You

At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for. 
PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.  

POSITION OVERVIEW:

As the Sr. Director/Vice President, Artificial Intelligence, you will lead the strategic development and enterprise-wide adoption of AI capabilities that support organizational transformation. Your role involves defining the AI vision, building a scalable roadmap, and driving execution across multiple business units. You will partner with Technology, Operations, Product, and executive leadership to identify high-value use cases, develop AI solutions, and integrate them into core business processes to deliver measurable results. This position requires a high level of autonomy, technical expertise, and strategic leadership, including assessing business needs, ensuring data readiness, designing and deploying models, overseeing MLOps practices, and implementing responsible AI principles. Your experience in AI, machine learning, data strategy, communication, stakeholder alignment, and solution delivery will be essential in enabling the organization’s transformation goals.

JOB FUNCTIONS:

(This list is not exhaustive and may be supplemented or changed as necessary.)

• Lead the strategic planning, development, and execution of the company’s AI roadmap and long-term innovation strategy.
• Identify, evaluate, and prioritize AI and machine learning opportunities that improve operations, automation, and business value.
• Apply structured methodologies to assess use case feasibility, technical readiness, adoption requirements, and expected ROI.
• Partner with Data Engineering and Technology teams to build and deploy scalable AI models, generative AI capabilities, and decision intelligence tools.
• Oversee all stages of the AI development lifecycle, including model design, testing, deployment, monitoring, retraining, and performance optimization.
• Develop and manage responsible AI frameworks that address transparency, risk, ethics, compliance, and governance.
• Conduct impact analyses and assess organizational readiness to adopt AI-driven processes and technologies.
• Create and deliver communication strategies to support AI adoption for leaders, teams, and stakeholders.
• Collaborate with business units to map workflows, redesign processes, and integrate AI-driven solutions into operations.
• Lead the design and implementation of training programs that support end-user adoption of AI tools.
• Build, develop, and mentor a high-performing AI organization across data science, machine learning, and applied AI disciplines.
• Partner with external technology providers, vendors, academic institutions, and research organizations to evaluate emerging AI technologies.
• Create metrics and dashboards to measure activation, performance, and business impact of AI solutions.
• Lead continuous improvement efforts through data analysis, root cause assessment, and iterative solution updates.
• Communicate complex technical concepts and model insights to executive leadership in clear, accessible language.
• Manage AI program budgets, resources, vendor contracts, and reporting requirements.

QUALIFICATIONS AND REQUIREMENTS:

Education:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required.
  Advanced degree preferred.

Technical Experience:

• 12 to 15 or more years of experience in AI, machine learning, data science, or advanced analytics.
• Demonstrated experience building and deploying machine learning models and generative AI systems in production environments.
• Deep understanding of modern AI techniques including large language models, natural language processing, deep learning, predictive modeling, and reinforcement learning.
• Experience implementing MLOps pipelines, model governance, and scalable AI systems in cloud environments such as Azure, AWS, or Google Cloud.
• Experience leading organization-wide AI or data transformation initiatives.
• Experience managing cross-functional teams and external partners or vendors.

Knowledge, Skills, and Abilities:

• Ability to define AI strategy, scope work, estimate effort, and drive execution.
• Ability to explain technical concepts to non-technical audiences and communicate with executives.
• Strong knowledge of AI ethics, responsible AI practices, and regulatory considerations.
• Ability to lead teams, influence stakeholders, and guide cross-functional efforts toward a shared vision.
• Strong analytical and problem-solving skills with the ability to interpret complex data and model results.
• Ability to manage multiple priorities in dynamic and fast-paced environments.
• Forward-thinking mindset with a focus on innovation and continuous learning.
• Strong presentation skills and experience delivering training or communication materials.
• Must be legally authorized to work in the United States without employer sponsorship now or in the future.

ESSENTIAL FUNCTIONS:

Physical Demands:

The physical demands described here are representative of the requirements that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee is regularly required to use a computer keyboard and mouse; reach with hands and arms; talk and listen. The employee is frequently required to walk and sit, as well as to lift and carry objects such as books and files weighing up to 25 pounds. The employee is occasionally required to stand, stoop, or kneel. Specific vision abilities required by this position include close vision and the ability to adjust focus.

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job, including moderate noise level, an indoor temperate environment, and light levels that are bright and conducive to minimal eye strain, typical for an office environment.

TOTAL REWARDS PROGRAM:

We define total rewards as compensation, benefits, remote work/flexibility, development, recognition and our culture with programs that support each of our reward pillars. This includes a market competitive base salary and annual incentive plan, robust benefit offerings, and ongoing recognition and career development opportunities. Employees also enjoy our generous flexible paid time off program, company paid holidays, flexible working hours, and fully remote work options for most positions and the ability to work “almost anywhere”. However, if a physical work location is more for you, we have office locations in Greater Boston; San Diego, CA; Boulder, CO; and India.

LEGAL STATEMENT:
 
Syner-G is proud to be an Equal Employment Opportunity and Affirmative Action employers. All employment decisions, including the recruiting, hiring, placement, training availability, promotion, compensation, evaluation, disciplinary actions, and termination of employment (if necessary) are made without regard to the employee’s race, color, creed, religion, sex, pregnancy or childbirth, personal appearance, family responsibilities, sexual orientation or preference, gender identity, political affiliation, source of income, place of residence, national or ethnic origin, ancestry, age, marital status, military veteran status, unfavorable discharge from military service, physical or mental disability, or on any other basis prohibited by applicable law. Syner-G is an E-Verify employer. 

Senior Software Engineer, Scientific Computing

About the Company 

The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear – even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers.

KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. In the six years since founding, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists.

KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery.

KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi.

About the Role

At KoBold we believe that a modern scientific computing stack will enable systematic mineral exploration and materially improve our rate of mineral discovery. This role is a key ingredient to this strategy. As a member of our scientific computing team, you will apply software engineering and machine learning to remote-sensing, drillhole, imaging, geophysics and other mineral exploration data in order to build scalable ML systems to help make high-speed, high-quality decisions for our mineral exploration projects. Collaborating with our exceptional team of data scientists and geologists, you will tackle complex scientific problems head-on and collectively pave the way for discoveries of vital energy transition metals like lithium, copper, nickel, and cobalt. Together we can shape the future of mineral exploration and contribute to building a sustainable world.

Responsibilities

• Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses.
• Build tooling to increase the velocity of our machine learning progress, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable ML pipelines; and organizing models and their outputs for repeatability and discoverability.
• In collaboration with data scientists, build models to make statistically valid predictions about the locations of economic concentrations of ore metals within the Earth’s crust.
• Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code
• Collaborate with data scientists, geoscientists and engineers to invent the modern scientific computing stack for mineral exploration
• Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery.  Travel is approximately twice per year depending on project needs.

Qualifications

Our ideal candidate will have:

• At least 5 years of experience as a software engineer, data scientist or ML engineer, though most great candidates will have closer to 10. 
• Track record of building production quality data processing solutions or tooling that have delivered business value
• Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches
• Proficiency in Python, ideally including array-based packages such as xarray and numpy
• Deep experience with measured scientific data
• Experience in visualizing scientific data for domain experts
• Experience in MLops and in the making of robust ML systems
• Drive to increase the velocity and effectiveness of our data scientists in both experimental and production workflows 
• Capacity to dive deep on novel challenging problems in applying ML to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources 
• Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)

Work practices and motivation:

• Ability to take ownership and responsibility of large projects.
• Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations.
• Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.
• Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.
• Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.
• Ability to independently prioritize multiple tasks effectively.

KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status.

This position is Full-time

The US base salary range for this full-time exempt position is $170,000 - $215,000

Location:  Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada

Senior Software Engineer, Decision Science

About the Company 

The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear – even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers.

KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. In the six years since founding, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists.

KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery.

KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi.

About the Role

At KoBold we believe that a modern scientific computing stack will enable systematic mineral exploration and materially improve our rate of mineral discovery. This role is a key ingredient to this strategy. As a member of our scientific computing team, you will apply decision science techniques in order to build scalable systems to help make high-speed, high-quality decisions for our mineral exploration projects. Collaborating with our exceptional team of data scientists, software engineers, and geologists, you will tackle complex scientific problems head-on and collectively pave the way for discoveries of vital energy transition metals like lithium, copper, nickel, and cobalt. Together we can shape the future of mineral exploration and contribute to building a sustainable world.

Responsibilities

• Architect, implement, and maintain decision science libraries that will be used in KoBold’s mineral exploration analyses.
• Build tooling to increase the velocity of our decision making, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable pipelines; and organizing ML models and their outputs for repeatability and discoverability.
• Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code
• Collaborate with data scientists, geoscientists and engineers to invent the modern decision science technology for mineral exploration
• Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery.  Travel is approximately twice per year depending on project needs.

Qualifications

Our ideal candidate will have:

• At least 5 years of experience in the field of decision science with a strong software engineering focus, though most great candidates will have closer to 10. 
• Track record of building production quality data processing solutions or tooling that have delivered business value
• Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches
• Proficiency in Python, ideally including array-based packages such as xarray and numpy
• Deep experience with measured scientific data
• Experience in visualizing scientific data for domain experts
• Experience in MLops and in the making of robust ML systems
• Drive to increase the velocity and effectiveness of our data scientists in both experimental and production workflows 
• Capacity to dive deep on novel challenging problems in applying decision science to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources 
• Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)

Work practices and motivation:

• Ability to take ownership and responsibility of large projects.
• Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations.
• Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.
• Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.
• Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.
• Ability to independently prioritize multiple tasks effectively.

KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status.

This position is Full-time

The US base salary range for this full-time exempt position is $170,000 - $215,000

Location:  Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada.