ml ops engineer

Openkyber

<div>Role :
Python/AI developer
Location :
Plano , TX
Duties/Key Responsibilities:
Working on projects leveraging your expertise in data science, artificial-intelligence and machine learning Assist in breaking down complex business problems, developing solutions, and delivering with a high degree of focus on client satisfaction. Conduct market research, develop a point-of-view and communicate effectively back to clients and stakeholders. Establish relationships with our clients at the appropriate levels, gain an understanding of the project work and problems encountered. Work with data sets of varying degrees of size and complexity including both structured and unstructured data. Piping and processing massive data-streams in distributed computing environments. Implement batch and real-time model scoring. Assemble large, complex data sets that meet functional / non-functional business requirements. Apply business knowledge to analyze data, develop reports and solve problems Perform ad hoc analyses of data depending on business needs. Participate in the analysis and resolution of issues related to information flow and content with data stakeholders.
Basic Qualifications:
<ul><li>5+ years of experience using Python to analyze disparate datasets</li>
<li>3+ years of experience supporting data science projects in a consulting environment.</li>
<li>Vector Database experience</li>
<li>3+ year(s) of experience participating in projects that focused on one or more of the following areas: Building/Enhancing LLMs LLM Data Injestion Statistics AI/ML ML Ops</li>
</ul>For applications and inquiries, contact: hirings@openkyber.com</div>

AI Agent Developer

Ingram Micro

<div>Accelerate your career. Join the organization that's driving the world's technology and shape the future.
Ingram Micro is a leading technology company for the global information technology ecosystem. With the ability to reach nearly 90% of the global population, we play a vital role in the worldwide IT sales channel, bringing products and services from technology manufacturers and cloud providers to business-to-business technology experts. Our market reach, diverse solutions and services portfolio, and digital platform Ingram Micro Xvantage&trade; set us apart. Learn more at www.ingrammicro.com
Come join our team where you&rsquo;ll make technology happen in surprising ways. Let&rsquo;s shape tomorrow - it&rsquo;ll be a fun journey!
Job Description
Employer: Ingram Micro Inc.
Job Title: ML Ops Engineers 
 
Job Location: Irvine, CA
Job Type: Full Time
Rate of Pay: $101,712-$123,614.40/yr
Job Duties: Responsible for accelerating Ingram&rsquo;s Artificial Intelligence solutions strategy. Develop new AI solutions, products, and insights to support key global initiatives in a complex multi-tier supply chain. Engage with a cross-functional group of stakeholders focused on advanced logistics, inventory, procurement, and warehouse projects in one of the world&rsquo;s largest logistics networks. Serve as the Subject Matter Expert (SME) for designing solutions that leverage AI/ML in the advanced logistics arena. Leverage technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. Drive the evolution of AI activities at Ingram Micro. Build analytics and AI/ML products or solutions. Perform design/implementation/consulting for Machine Learning/AI/Deep Learning solutions. Utilize experience with Learning frameworks, technical architecture, design, deployment and operations for AI platforms, standards, protocols, and devices. Research data to discover hidden patterns. Collaborate effectively across organizational boundaries, build relationships, and import/export talent and ideas to achieve a broader organizational goal. Develop experimental and analytic plans for data modeling processes, use of strong baselines, accurately determine cause and effect relationships. Apply data science techniques to real-world business challenges. Use data visualization tools. Present complex technical concepts to broad audiences in a simplified format.
Employer will accept a Bachelor's degree in Computer Science, Computer Engineering, Statistics, Mathematics or related field and 3 years of experience in the job offered or in a Data Scientist-related occupation.
Telecommuting / working from home may be permissible pursuant to company policy.
CONTACT: Search by title and apply online at https://www.ingrammicro.com/en-us/careers/work-for-us
At Ingram Micro certain roles are eligible for additional rewards, including merit increases, annual bonus or sales incentives and long-term incentives. These awards are allocated based on position level and individual performance. U.S.-based employees have access to healthcare benefits, paid time off, parental leave, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, and wellbeing benefits, among others.
This is not a complete listing of the job duties. It&rsquo;s a representation of the things you will be doing, and you may not perform all these duties.
Please be prepared to pass a drug test and successfully pass a pre-employment (post offer) background check.
Ingram Micro Inc. is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law.</div>

ML Ops Engineers

Ford Motor Company

<div>
 
 Job Description
 
 
 
 We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we&rsquo;re all a part of something bigger than ourselves. Are you ready to change the way the world moves?
 
 
 The Global Data Insights and Analytics (GDI&amp;A) Design Cost and Complexity Analytics team is looking for a data scientist with expertise developing and deploying analytics solutions. As a member of this team with varied strengths, you will have the opportunity to work with some of the brightest global domain experts in vehicle cost/quality and connectivity who are transforming the automobile industry.
 
 
 Our ideal candidate will lead or assist in AI/ML model development and deployment to support vehicle quality improvement and design cost reduction, by using connected vehicle data and other data sources to predict customer usage. You will be encouraged to work with AI/ML experts and IT team to choose the right software architecture and implement the AI/ML solution. We are seeking independent problem solvers with a technical mentality who have a passion for learning and applying groundbreaking technologies. This role requires a strong blend of data science expertise and software engineering skills for end-to-end ML Ops and front-end development.
 
 
 
 Responsibilities
 
 
 
 
 What you'll do...
 
 
 
 You will be responsible for providing the data analytics support for projects, including assembly of data for building models, building data pipelines, and performing predictive/prescriptive analytics, and building POC web applications. More specifically, you will:
 
 
 <ul>
 <li>
 Collaborate with Product Development and Quality experts to understand their requirements and overall business needs and translate high-level ideas into well-defined mathematical problems
 </li>
 <li>
 Collaborate with IT partners to ensure that the AI/ML solutions are deployed seamlessly
 </li>
 <li>
 Identify key data elements to extract/decode/analyze. Understand which elements of large data sets can be most effectively demonstrated in the analytic models and what potentially useful information may be missing.
 </li>
 <li>
 Apply advanced analytical solutions (including machine learning and statistical models), and conduct analysis that consists of problem formulation, data extraction and pre-processing, modeling, validation, ongoing work, and presentations.
 </li>
 <li>
 Manipulate high-volume, high-dimensional structured and unstructured data from a variety of sources and implement algorithms to identify anomalies, relationships, and trends
 </li>
 <li>
 Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing concrete business insight
 </li>
 <li>
 Explore new technologies and analytic solutions for use in quantitative model development and deployment
 </li>
 <li>
 Develop complete system designs that include data, pre-processing, modeling, optimization, post-processing, and interfaces for user interaction, including front-end development.
 </li>
 <li>
 Interpret modeling results and communicate them to technical and non-technical audiences, multi-functional teams, and leadership
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 You'll have...
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Electrical Engineering, or a related field
 </li>
 <li>
 1+ years experience in a data analytics role including running queries, compiling data, and manipulating data from separate sources to form unified sets for analysis.
 </li>
 <li>
 1+ years experience in predictive analytics including machine learning and experience writing algorithms in Python, Scala, or similar languages.
 </li>
 <li>
 1+ years experience in at least one of the following languages: Python, R, SQL, or similar languages.
 
 
 
 </li>
 </ul>
 
 Even better, you may have...
 
 
 
 <ul>
 <li>
 MS or PhD in Computer Science, Electrical Engineering or a related field
 </li>
 <li>
 2+ years of experience with Python, SQL, Spark, Hadoop, or Google Cloud Platform
 </li>
 <li>
 2+ years of experience with Machine Learning methods and tools, including but not limited to: linear and nonlinear regression, classification, and clustering (Relevant university course projects qualify)
 </li>
 <li>
 1+ year of work experience (in a non-academic setting) involving complex quantitative modeling and analysis in any of the areas mentioned under Basic Qualifications
 </li>
 <li>
 1+ year of experience or equivalent in creating and deploying Agentic AI solutions in real world industrial setting
 </li>
 <li>
 Demonstrated ability in the application of Machine Learning to real-world industrial settings with large scale data
 </li>
 <li>
 Proficient with version control systems such as Git, as well as agile software development and DevOps tools
 </li>
 <li>
 Excellent programming skills, particularly interface development to generate data visualizations and to extract insights from large complex data sets, is very desirable
 </li>
 <li>
 Strong oral, written, and interpersonal communication skills and an ability to work in a collaborative team setting
 </li>
 <li>
 Familiarity with web development backend frameworks such as Python Flask or Java SpringBoot, and frontend frameworks such as Angular
 </li>
 <li>
 Comfortable working in a fast-paced and innovative environment where problems are not always well-defined
 </li>
 <li>
 Well-organized, a self-starter, independent and ready to work with minimal direction
 
 
 
 </li>
 </ul>
 You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
 
 
 As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder&hellip;or all of the above? No matter what you choose, we offer a work life that works for you, including:
 
 
 <ul>
 <li>
 Immediate medical, dental, vision and prescription drug coverage
 </li>
 <li>
 Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
 </li>
 <li>
 Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
 </li>
 <li>
 Vehicle discount program for employees and family members and management leases
 </li>
 <li>
 Tuition assistance
 </li>
 <li>
 Established and active employee resource groups
 </li>
 <li>
 Paid time off for individual and team community service
 </li>
 <li>
 A generous schedule of paid holidays, including the week between Christmas and New Year&rsquo;s Day
 </li>
 <li>
 Paid time off and the option to purchase additional vacation time.
 
 
 
 </li>
 </ul>
 For a detailed look at our benefits, click here:
 
 
 https://fordcareers.co/GSR-HTHD
 
 
 This position is a range of salary grades 7-8.
 
 
 <ul>
 <li>
 Note: This is a hybrid role, you are expected to relocate if you are not within commutable distance, and responsible to be on site at least 4 days a week
 
 
 
 </li>
 </ul>
 Visa sponsorship is not available for this position.
 
 
 Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
 
 
 We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
 
 
 #AH1
 
 
</div>

Data Scientist

Valley Bank

<div><div>Responsibilities include but are not limited to:</div>
<ul><li>Design and implement agentic AI workflows using UiPath and Salesforce Agentforce, combining LLMs, rules, APIs, and ML models for end‑to‑end automation.</li>
<li>Develop reusable agent frameworks and components to standardize and accelerate AI solution delivery.</li>
<li>Build, train, and deploy machine learning models (classification, regression, time‑series, anomaly detection) using DataRobot, leveraging Snowflake and Databricks for large‑scale data engineering.</li>
<li>Integrate ML models into enterprise workflows, APIs, and downstream applications.</li>
<li>Engineer integrations across enterprise systems using REST APIs, event-driven architectures, and robust data pipelines.</li>
<li>Support CI/CD and MLOps practices for scalable model deployment, monitoring, retraining, and lifecycle management.</li>
<li>Ensure compliance with AI governance and model risk policies, maintaining monitoring, documentation, and audit readiness.</li>
</ul>Requirements:
<div><div>Required Skills:</div>
<ul><li>Hands-on experience with agentic AI, orchestration, or intelligent automation platforms (UiPath strongly preferred).</li>
<li>Strong experience building and deploying ML models using DataRobot or comparable platforms.</li>
<li>Solid experience working with Snowflake and/or Databricks for data and ML workloads.</li>
<li>Proficiency in Python; experience with SQL and API-based integrations.</li>
<li>Strong understanding of ML lifecycle, model evaluation, and production deployment.</li>
<li>Exposure to LLMs, prompt engineering, RAG, and AI agents in enterprise environments.</li>
<li>Experience operating AI solutions in regulated industries (financial services, healthcare, etc.).</li>
<li>Familiarity with MLOps, feature stores, and model monitoring practices.</li>
</ul><div>Preferred Skills:</div>
<ul><li>Experience with Agentic AI and AI workflow orchestration.</li>
<li>Exposure to Generative AI (LLMs, prompt engineering, copilots, or AI assistants).</li>
<li>Experience building or supporting Intelligent Document Processing (IDP) solutions.</li>
<li>Knowledge of OCR, Computer Vision, and document classification/extraction techniques.</li>
<li>Familiarity with Machine Learning concepts, model integration, or ML platforms.</li>
<li>Experience integrating AI and automation solutions with enterprise platforms (e.g., CRM, ServiceNow, core banking systems).</li>
</ul><div>Required Experience:</div>
<ul><li>Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.</li>
<li>Minimum of 6 years of experience building production-grade AI, ML, or automation solutions and AI Technology.</li>
</ul><div>Preferred Experience:</div>
<ul><li>Master's in Computer Science, MIS, or related degree.</li>
<li>Financial industry or banking background.</li>
<li>Experience with Salesforce Agentforce or Salesforce platform integrations.</li>
<li>Experience contributing to AI architecture standards or internal platforms.</li>
</ul>
</div> 
Additional Details : At Valley Bank, we believe in people's growth potential. We invest in it. We protect it. We focus it. For nearly 100 years, we've been the Bank that clients from every industry turn to for our expertise, strategies, and advice-building the kind of trust that can fuel every goal. We are the leading relationship bank built for growth-with over $60 billion in assets, 3,800 experts, and more than 200 consumer branches and commercial banking offices in communities across the US. At Valley, we're all driven by an ambition that goes deeper than just having a job. That's why when you work for us, we make it our goal to help you focus on what drives you-working to turn your passions and strengths into assets you can use to propel your ambitions and build the professional legacy you want. Because when we say we're a relationship bank built for growth, that's not just reserved for our clients-that includes all our associates as well. The Senior AI Engineer will design, build, and operationalize agentic AI workflows and machine learning solutions across the enterprise. This role sits at the intersection of intelligent automation, generative AI, and enterprise data platforms, and will play a key role in scaling AI-driven workflows using UiPath, Salesforce Agentforce, DataRobot, Snowflake, and Databricks. You will partner closely with product, operations, risk, and technology teams to deliver AI systems that are production-grade, governed, and value-driven. 
 
Pay Transparency In order to support the Fair Compensation Strategy by the US Govt., HR Dept., clients are required to adhere to &quot;Pay Transparency Law&quot;; in the impacted states; that have mandated the employers to list the salary ranges in Job advertisements or postings for job opportunities and Job promotions.</div>

Senior AI Engineer

Value Engineering

Reporting to AI Lead / Solution Architect, this is a senior technical leadership role responsible for: Designing and deploying state-of-the-art LLMs and multi-modal AI models. Implementing agentic AI systems with RAG, self-RAG, and memory-optimized architectures. Leading cloud-based GPU LLM training pipelines, including data labeling, preprocessing, model training, and post-processing. Extending AI models into front-end applications and back-end pipelines. Managing staging, development, and production environments with SSH deployment and editing. Driving complex problem-solving, critical thinking, and innovative AI solutionsKey Responsibilities1. LLM Cloud Training &amp; Pipelines (Mandatory)Design and deploy LLM training pipelines on cloud GPU infrastructure. Manage data labeling, preprocessing, and post-processing for training datasets. Optimize model training, memory usage, and inference efficiency. Implement RAG-based pipelines, agentic RAG, and self-RAG for knowledge augmentation.2. Deep Learning &amp; Model DevelopmentResearch, design, and implement Transformers, Vision Transformers, Diffusion Models. Optimize SAM models for tabular and image data, including preprocessing and post-processing. Implement multi-modal AI pipelines (text, image, video). Develop agentic AI models with adaptive memory and reasoning.3. Agentic AI &amp; OrchestrationDesign agent frameworks with orchestration, inter-agent communication, and protocol management. Integrate LangChain, LangGraph, or custom agent pipelines. Ensure AI agents are robust, scalable, and production-ready.4. Machine Learning for Real-World DataImplement ML models for tabular, image, and multi-modal data. Preprocess, normalize, and feature-engineer datasets for SAM and other model types. Translate research models into production pipelines with RAG augmentation.5. Front-End &amp; Back-End AI IntegrationExtend AI models into front-end applications (interactive AI features). Integrate AI models into back-end services for low-latency inference. Ensure seamless integration between AI models and application architecture.6. Production AI Infrastructure &amp; DeploymentDeploy AI models on MCP / GPU servers, distributed clusters, or cloud infrastructure. Manage staging, dev, and production environments, including SSH deployment, editing, and version control. Implement monitoring and observability using Prometheus, Grafana, and custom dashboards. Maintain CI/CD for AI models, training pipelines, and data workflows, including Git/GitHub workflow management.7. Research to Production TranslationBring experimental AI models into production-grade systems. Validate model performance, reliability, and safety. Implement reproducibility, versioning, and automated retraining pipelines.8. Mentorship &amp; LeadershipMentor junior AI engineers and researchers. Establish best practices for AI experimentation, deployment, and RAG/agentic architectures. Contribute to AI roadmap and enterprise AI strategy.Required Experience5+ years AI / Deep Learning / Research &amp; Production experience. Mandatory: Hands-on experience in LLM training pipelines, including cloud GPU infrastructure, data labeling, preprocessing, training, and post-processing. Deep knowledge of Neural Networks, Transformers, LLMs, Vision Transformers, Diffusion Models, Agentic AI, RAG/self-RAG pipelines. Hands-on experience with SAM models, tabular data ML, and preprocessing pipelines. Experience managing staging, dev, and production environments with SSH deployment, editing, and Git/GitHub workflow. Strong Computer Vision and Image Processing skills. Experience with agent orchestration, LangChain, LangGraph, and protocol optimization. Proven problem-solving, critical thinking, and innovative AI solution delivery. Experience integrating AI into front-end and back-end systems.Preferred ExperienceExperience with generative AI, diffusion models, multi-modal agents. Optimizing LLM memory, inference, and fine-tuning at scale. Experience in production RAG pipelines and knowledge-augmented AI systems.Application Question(s):<ul><li>Are you available to work from 2:00 PM &ndash; 11:00 PM shift Monday to Friday with alternate Saturday?</li></ul><ul><li>Are you comfortable working onsite from Bahria Phase 4, Rawalpindi?</li></ul><ul><li>How many years of experience do you have as AI Engineer?</li></ul>Work Location: In person

Lead AI Engineer

Valeo

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 <ul>
 <li>
 End-to-End AI/ML Solution Delivery
 </li>
 <li>
 Design &amp; Develop~ Design, develop, industrialize, and deploy advanced predictive and machine learning models (e.g., supervised/unsupervised, scoring, NLP, recommendation &amp; personalization systems,classification, regressions and diagnostic).
 </li>
 <li>
 Build &amp; Innovate~ Build, maintain, and improve robust, scalable data and ML pipelines, from exploration to production (API, CI/CD, MLOps). Construct and innovate with Generative AI systems (LLMs, RAG, fine-tuning) to enhance product features and internal processes.
 </li>
 <li>
 Ensure Quality~ Guarantee solutions are robust, scalable, and production-ready by applying best practices in software engineering and MLOps (e.g., containerization, monitoring, versioning).
 </li>
 <li>
 Own &amp; Deploy~ Own your models end-to-end, from idea generation and prototyping to deployment, monitoring, A/B testing, and continuous improvement. Drive the integration of models into production-ready pipelines, establishing and managing version control, validation, and automated testing strategies.
 </li>
 <li>
 Technical Strategy &amp; Leadership
 </li>
 <li>
 Problem Framing~ Frame use cases with business teams, validate data availability, and use rigorous analysis to break down ambiguous business questions into testable hypotheses and concrete data science projects. Define success metrics (KPIs) upfront to ensure every project has a measurable business impact.
 </li>
 <li>
 Technology Assessment~ Lead "make-or-buy" decisions by evaluating the trade-offs between building proprietary models versus integrating third-party AI services, always aligning with business objectives for speed, cost, and long-term value.
 </li>
 <li>
 Mentorship &amp; Standardization~ Act as a technical reference, providing leadership and mentorship to junior data scientists through code reviews and knowledge sharing. Drive technical excellence by standardizing frameworks and improving our technical stack, modeling approaches, and deployment practices.
 </li>
 <li>
 Innovation~ Stay ahead of market trends and conduct active research on the latest advancements in AI/ML to identify and propose innovative approaches and new use cases. This includes attending conferences,, and participating in meetups and internal learnshops.
 </li>
 <li>
 Collaboration &amp; Influence
 </li>
 <li>
 Data-Driven Collaboration~ Act as the analytical authority within cross-functional teams (Product, Engineering, Business). Challenge existing assumptions with data, guide strategic decisions with analytical evidence, and ensure model outputs are directly integrated into business workflows.
 </li>
 <li>
 Insightful Communication~ Go beyond just presenting results. Clearly explain the "why" behind your model's logic, its limitations (e.g., biases, confidence levels), and the trade-offs between different analytical approaches to both technical and executive audiences.
 </li>
 <li>
 Actionable Visualization~ Create clear dashboards and visualizations that tell a story with the data, empowering stakeholders to make data-informed decisions independently.
 </li>
 <li>
 Cross-Functional Leadership~ Lead collaboration with IT and Data Engineering teams to enhance data accessibility, harmonization, pipeline robustness, and streamline model deployment.
 </li>
 <li>
 Data Strategy~ Evaluate data availability, coverage, and quality, proposing pragmatic approaches for calibration, substitution, or enrichment when datasets are incomplete or imperfect.
 
 
 </li>
 </ul>
 
 
 
 Professional
 
 
 Experience
 
 
 
 
 
 We are looking for a candidate who embodies three core strengths~
 
 
 <ul>
 <li>
 Technical &amp; Execution Excellence You are a master builder who ships robust, production-grade solutions.
 </li>
 <li>
 After a master degree and PhD , you bring 5+ years of applied experience as a Data Scientist, with a proven track record of taking complex Machine Learning projects from initial POC to full production deployment.
 </li>
 <li>
 Your experience comes from a fast-paced, commercial environment (such as E-commerce, FinTech, Online Travel, SaaS, or modern Tech Consulting), where you have successfully built and shipped models for dynamic pricing, demand forecasting, or resource optimization.
 </li>
 <li>
 Your technical toolkit is extensive, with an excellent mastery of Python and its core data science libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, pandas, NumPy).
 </li>
 <li>
 You have strong knowledge of the full MLOps and Data Engineering lifecycle, including SQL, containerization (Docker), workflow orchestration (Airflow), CI/CD, and model deployment/serving (MLflow, Kubernetes, REST APIs).
 </li>
 <li>
 You have a deep understanding of Generative AI architectures and workflows (embeddings, RAG, fine-tuning) and have experience with GenAI/LLM projects.
 </li>
 <li>
 You are adept at creating clear, insightful visualizations using tools like Looker, Tableau, or Power BI and applying Agile/scrum methodologies to deliver results iteratively.
 </li>
 <li>
 You have hands-on experience working with large-scale datasets in cloud environments (e.g., AWS, GCP).
 </li>
 <li>
 Strategic &amp; Business Acumen You think like a business owner and translate complex data into tangible value.
 </li>
 <li>
 You have a proven ability to deconstruct ambiguous business problems into a clear analytical framework, defining testable hypotheses and the KPIs that will measure success.
 </li>
 <li>
 You demonstrate strong project management skills, taking ownership of the entire project lifecycle to ensure solutions are delivered on time and create measurable business impact.
 </li>
 <li>
 You practice statistical rigor, going beyond model accuracy to validate choices, quantify uncertainty, and ensure the reliability and fairness of your results in a real-world context.
 </li>
 <li>
 You have led root-cause investigations, using data to diagnose why business metrics deviate from expectations and recommending a clear solution.
 </li>
 <li>
 You demonstrate exceptional business impact translation, turning complex model outputs into a compelling narrative that influences leadership-level decisions.
 </li>
 <li>
 Leadership &amp; Collaborative Influence You are a natural coach and communicator who elevates the entire team.
 </li>
 <li>
 You possess strong leadership and mentoring skills with a genuine passion for sharing knowledge, helping others grow, and fostering a collaborative team environment.
 </li>
 <li>
 Your communication skills are excellent, giving you the ability to tell a compelling story with data and distill complex topics into simple, clear explanations for any audience.
 </li>
 <li>
 You have a proactive, autonomous, and results-oriented mindset. You are intellectually curious, pragmatic, and thrive in a fast-paced, collaborative setting.
 </li>
 <li>
 You have the business acumen to understand complex challenges and translate them into adapted technical solutions.
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 Software Development
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-02-22
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

Senior AI Technical Lead, Valeo Service

Shift Technology

<div><div>Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk - driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the world's leading insurers, Shift delivers AI when and where it matters most, at scale and with proven results.

Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance.</div>
About the Team
<ul>
<li>This role is part of our Data Science team which is the largest team in our organization consisting of over 200+ Data Scientists throughout the world.</li>
<li>Our Data Scientists work in a full lifecycle role and on a broad range of subjects acquiring extensive technical and professional experience in data science, data engineering, coding, business understanding and client engagement.</li>
<li>Our company is small enough that each person's achievements has an impact on our overall performance, yet big enough to be a world leader and innovator in our domain.</li>
<li>As a member of the data science team, you will be working alongside our technical experts and your role will be key to rolling out our enterprise level solutions to our clients.</li>
</ul>
Key Responsibilities
<ul>
<li>Your role will be to actively contribute to the US- Insurance roadmap and clients, and working on various data types such as structured data, free text, documents and images.</li>
<li>Build and productionize data pipelines (structured, text, documents, images) optimized for LLMs and multi-modal models.</li>
<li>Design, develop and deploy LLM-based solutions (RAG, embeddings, instruction tuning) for subrogation, claims handling, document understanding, and related use cases.</li>
<li>Experiment with the latest in Agentic AI technologies (Langchain/Langgraph, OpenAI Agent SDK, MCP, A2A) and develop MVP for the next generation of autonomous subrogation solutions.</li>
<li>Develop &quot;Chain-of-Thought&quot; and &quot;ReAct&quot; prompting strategies to ensure the agent can justify its liability percentages based on the Comparative Negligence laws of different jurisdictions.</li>
<li>Create custom &quot;tools&quot; for the agent, allowing it to query internal databases, call external weather APIs, or calculate impact force based on telemetry data.</li>
<li>Establish rigorous evaluation frameworks (LLM-as-a-judge) to ensure the agent's decisions are unbiased, legally sound, and explainable.</li>
<li>Ensure responsible-AI practices: privacy, hallucination mitigation, explainability and compliance.</li>
<li>Lead client workshops, present prototypes, gather feedback and help define roadmap priorities.</li>
</ul>
WHAT WE ARE LOOKING FOR

We are looking for candidates with diverse skills to help us build excellent technology solutions for our clients and be proficient in the following skills:
<ul>
<li>Expert proficiency in production-level object-oriented programming (OOP) for building scalable and reliable systems.</li>
<li>Proven hands-on experience with Large Language Models (LLMs) and generative AI techniques (including RAG, embeddings, prompt engineering, and model tuning), leveraging frameworks such as OpenAI/Anthropic or open-source variants.</li>
<li>Solid foundation in ML fundamentals with practical experience in the full machine learning lifecycle, including model evaluation, monitoring, versioning, and deployment in production environments.</li>
<li>Experience designing and implementing robust data pipelines for document, OCR, and multi-modal data workflows.</li>
<li>Agentic Frameworks: Experience with integrating frameworks like LangChain/LangGraph, OpenAI Agent SDK, CrewAI, A2A/MCP with Databricks or Azure-hosted models (e.g., DBRX, OpenAI GPT-5.3, Anthropic Claude, Google Gemini).</li>
<li>Demonstrated ability to effectively engage with clients, translate complex business needs into clear, actionable technical solutions, and manage stakeholder expectations.</li>
</ul>
Highly Desired Skills
<ul>
<li>Databricks Ecosystem: Deep expertise in Mosaic AI (formerly MosaicML), Unity Catalog, and Delta Lake. Good understanding of Spark data architecture is a plus.</li>
<li>Experience using MLflow for the full lifecycle: from experiment tracking and prompt engineering in the AI Playground to model evaluation.</li>
</ul>
 #LI-MG1
<div>
#LI-HYBRID</div>
<div>
To support our permanent, full time employees at every stage of their careers and lives, we provide a competitive total rewards and benefits package. Here are the global benefits we'd like to highlight:
<ul>
<li>Flexible remote and hybrid working options</li>
<li>Competitive Salary and a variable component tied to personal and company performance</li>
<li>Multiple Learning and Development opportunities, including Focus Fridays, a half-day each month to focus on learning and personal growth</li>
<li>Generous PTO and paid holidays</li>
<li>Mental health benefits</li>
<li>2 MAD Days per year (Make A Difference Days for paid volunteering)</li>
</ul>
Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details.

At Shift we strive to be a diverse and inclusive workforce. We welcome applications from and hire people who will contribute to the diversity of our company, without regard to race, color, religion, marital status, age, national or ethnic origin, physical or mental disability, medical condition, pregnancy, genetic information, gender identity or expression, sexual orientation, or other non-merit criteria.

Shift Technology is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and employment process. Should you require accommodation, please email accommodation@shift-technology.com and we will work with you to meet your accessibility needs.

Please be aware of scammers and only trust correspondence that comes from emails ending in &quot;shift-technology.com&quot;. We will never do initial outreach to you via Whatsapp/Text/SMS, never ask for banking information or personal identification numbers (ex. Social Security Number) as part of our recruitment process.

Shift Technology does not accept unsolicited CVs from recruiters or employment agencies in response to the Shift Technology Careers page or a Shift Technology social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Shift Technology.</div></div>

Data Scientist / Engineer

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