Product Pricing Analyst

Manager, Industrial and Employee Relations

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Partner Solutions Engineer - IOT

 IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Staff Simulation Engineer - CFD

Account Executive - Architecture

Responsibilities: <ul><li>Analyze industry pricing standards and competitors to set optimal pricing strategies.</li><li>Harvest and consolidate data from various sources to support pricing decision-making.</li><li>Maintain product pricing routinely in internal systems.</li><li>Manage pricing requests both online and offline via tools.</li><li>Identify low-margin business segments and collaborate with Product Managers to resolve issues.</li><li>Monitor pricing agreement performance and ensure adherence to expected margins.</li><li>Apply advanced analytics to identify pricing issues and opportunities.</li><li>Develop dashboards and reports that support strategic pricing decisions.</li><li>Explore innovative pricing techniques, such as AI-driven models, competitor benchmarking, and cross-functional data integration.</li><li>Communicate and align pricing strategies across departments: Sales, PM, Customer Care, and Finance.</li><li>Simplify and clearly communicate pricing decisions and methodologies to stakeholders.</li><li>Incorporate market insights and business rules into pricing logic.</li><li>Recommend pricing actions to capture market opportunities and improve profitability.</li></ul> Requirements: Experience: <ul><li>Minimum 5- 6 years of experience in pricing analysis, business analysis, commercial strategy, or a related field.</li></ul> Education: <ul><li>Bachelor’s degree or higher in Economics, Finance, Business, Statistics, or a related field.</li></ul> Skills: <ul><li>Strong analytical, strategic thinking, and problem-solving skills.</li><li>Proficiency in Excel and data visualization tools (e.g., Power BI).</li><li>Experience working across business units and aligning stakeholder objectives.</li><li>Ability to present complex data in a clear, simplified format.</li></ul>

Responsibilities: Grievance &amp; Compliance Leadership: <ul><li>Lead end-to-end employee misconduct investigations (preliminary and detailed), ensuring fairness, consistency, and legal compliance across all cases.</li><li>Own full disciplinary lifecycle: recommend actions, approve issuance of show cause/warning/dismissal letters, and maintain robust, auditable records.</li><li>Drive periodic compliance audits across contract labor suppliers (security, canteen, uniform vendors) and ensure timely corrective action on non-conformities.</li><li>Conduct due diligence and performance reviews of foreign operator agencies; submit data-driven recommendations for contract renewals or terminations.</li></ul> Policy &amp; Process Ownership: <ul><li>Manage centralized document control for all HR policies, procedures, and operational guidelines — ensuring accessibility, version control, and alignment with evolving legal standards.</li><li>Design and deliver compliance training programs for managers and employees, covering HR policy, performance management, and labor law essentials.</li><li>Act as the go-to subject matter expert on employment law, IR best practices, and grievance resolution frameworks.</li></ul> Union Engagement &amp; Strategy: <ul><li>Lead plants transition into a unionized environment: educate leaders and HR on union dynamics, negotiation frameworks, and collaborative engagement models.</li><li>Build and sustain a constructive union relationship — balancing business needs with employee representation through regular dialogue, transparency, and mutual respect.</li><li>Anticipate union-related risks and opportunities; advise leadership proactively on IR positioning and response strategies.</li><li>Drive union readiness programs, including leadership coaching, communication protocols, and scenario planning.&nbsp;</li></ul> Canteen Management: <ul><li>Lead vendor governance for contract labor and canteen operations. Monitor service levels, hygiene, and employee satisfaction; drive timely audits, feedback loops, and improvements.</li></ul> Hostel &amp; Foreign Worker Management (End-to-End): <ul><li>Manage full lifecycle of foreign worker operations: manpower planning, documentation, immigration processes, hostel inspections, welfare coordination, and compliance with regulatory and internal standards.</li><li>Ensure foreign workers are treated with dignity and respect; champion human rights standards and ethical labor practices.</li><li>Coordinate with embassies, Ministry of Home Affairs, Department of Immigration, and labor agencies to ensure seamless processes and timely resolution of issues.</li><li>Oversee hostel living conditions, safety, and welfare programs; act as the primary point of contact for foreign worker concerns.</li></ul> Compliance Audits &amp; Risk Management: <ul><li>Lead and coordinate audits related to labor compliance, human rights, and ethical sourcing across all third-party providers.</li><li>Ensure the plant is audit-ready at all times; track and close findings with urgency and rigor.</li><li>Stay current on evolving labor regulations and proactively adjust policies and practices to mitigate risk</li></ul> Requirements: <ul><li>Bachelors degree in Human Resource Management, Business Administration, Industrial Relations, or related discipline.</li><li>7–10 years of HR experience, with deep exposure to industrial relations, employee relations, labor law, and HR compliance—preferably in a manufacturing, unionized, or FMCG environment.</li><li>Proven track record of managing complex disciplinary cases, union negotiations, and IR matters with sound judgment and integrity.</li><li>Strong working knowledge of Malaysian labor law, Employment Act, Industrial Relations Act, and related regulations.</li><li>Advanced proficiency in Microsoft Office (Excel, Word, PowerPoint); able to prepare reports, dashboards, and present findings with clarity.</li><li>Familiar with HR systems, documentation best practices, and audit standards.</li><li>Excellent stakeholder management and interpersonal skills; able to influence, negotiate, and build trust across all levels—from frontline employees to senior leaders.</li></ul>

Responsibilities: <ul><li>We are seeking a Solutions Engineer - Artificial Intelligence (AI) Practitioner to join our dynamic sales team. As an SE (AI Practitioner), you will consult and drive the adoption of our AI solutions across various industries.</li><li>You will identify potential clients, understand their specific needs, and provide tailored AI solutions that enhance their business operations.</li><li>This role requires a deep understanding of AI technologies, real world deployment experience and expert capability to relay business and technical concepts to a diverse audience.</li><li>The Cloud and AI Infrastructure team is responsible for helping customers change their business using Client technology in the data center and on cloud. The team works with customers, partners and engineering teams to take customer problems and turn them into business advantage.</li></ul> Requirements: Minimum Qualifications: <ul><li>10+ years of technology consulting experience (preferably in systems, software, data, analytics and AI).</li><li>Good understanding of programming/scripting languages</li><li>Ability to provide detailed and consumable documentation and standard methodologies for deployment around application acceleration, automation/management efficiencies, enterprise, and AI/ML solutions.</li><li>Be able to develop and showcase real world examples of how AI technology can help businesses thrive and solve problems.</li><li>Excellent presentation skills – ability to value-sell and deliver engaging workshops to both technical and non-technical audiences on AI and/or infrastructure topics. Preferred</li><li>Bachelors Degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. Advanced degree in Data Science is a plus.</li><li>Experience with AI relevant infrastructure, including Networking (InfiniBand and RoCE), Storage (FC, IP and scale out) and AI accelerators (GPUs etc).</li><li>In-depth understanding of AI models, including but not limited to GPT, Llama, Resnet or similar.</li><li>Experienced with data storage and management (SQL, NOSQL, Vector, BigQuery etc) and AI/ML frameworks (scikit-learn, TensorFlow, PyTorch, Jupyter, NIMS and NVAIE etc).</li><li>Expertise in training and fine-tuning AI models on premise or in cloud environments.</li><li>Familiarity with containerization (k8 etc).</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Dashboard Design and Development: Design, develop, and maintain interactive and user-friendly dashboards in PowerBI and Looker, focusing on clarity, performance, and data accuracy.&nbsp;</li><li>Data Lake Integration: Connect to and leverage data from various data lake sources on GCP, ensuring seamless data flow for visualization purposes.&nbsp;</li><li>Semantic Model Development: Develop and maintain robust semantic models in Looker (LookML) and PowerBI, ensuring data consistency, accuracy, and ease of use for reporting and analysis. This includes defining dimensions, measures, relationships, and calculations.&nbsp;</li><li>Machine Learning and GenAI Visualization: Create compelling visualizations to effectively communicate the results, performance, and insights derived from machine learning models and GenAI applications. This may involve visualizing model predictions, feature importance, natural language processing outputs, and other relevant data.&nbsp;</li><li>GCP Expertise: Utilize your strong understanding of GCP services to access, process, and prepare data for visualization. This may involve working with services such as BigQuery, Cloud Storage, and potentially data engineering pipelines built on GCP.&nbsp;</li><li>Collaboration: Partner closely with data scientists, data engineers, product managers, and business stakeholders to understand their data visualization needs and translate them into effective visual solutions.&nbsp;</li><li>Requirements Gathering: Elicit and document visualization requirements from various stakeholders, ensuring alignment with business objectives.&nbsp;</li><li>Performance Optimization: Optimize dashboard and visualization performance to ensure fast load times and efficient data rendering.&nbsp;</li><li>Data Quality Assurance: Ensure the accuracy, consistency, and reliability of data presented in visualizations.&nbsp;</li><li>Best Practices and Standards: Establish and enforce data visualization best practices and standards across the organization.&nbsp;</li><li>Training and Support: Provide guidance and support to other team members on data visualization tools and techniques.&nbsp;</li><li>Continuous Learning: Stay up to date with the latest trends and advancements in data visualization, PowerBI, Looker, GCP, and related technologies, particularly in the context of AI/ML.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s or master’s degree in computer science, Data Science, Statistics, Information Systems, or a related field.&nbsp;</li><li>Minimum of 3 years of experience as a Visualization Expert, Data Visualization Engineer, or a similar role.&nbsp;</li><li>Proven expertise in designing and developing interactive dashboards and reports using PowerBI and Looker.&nbsp;</li><li>Strong experience in connecting to and working with data lakes, preferably on the Google Cloud Platform (GCP).&nbsp;</li><li>Solid understanding and hands-on experience in developing semantic models, particularly with LookML in Looker and data modeling within PowerBI.&nbsp;</li><li>Preferable experience in creating visualizations specifically for machine learning and GenAI applications, understanding the nuances of presenting model outputs and insights.&nbsp;</li><li>Proficiency in SQL for data extraction and manipulation.&nbsp;</li><li>Familiarity with data warehousing concepts and data modeling techniques.&nbsp;</li><li>Experience with data preparation, ELT (preferred) / ETL processes.&nbsp;</li><li>Strong analytical and problem-solving skills with the ability to interpret complex data.&nbsp;</li><li>Excellent communication and presentation skills, with the ability to convey technical information to both technical and non-technical audiences.&nbsp;&nbsp;</li><li>Ability to work independently and collaboratively in a fast-paced environment.&nbsp;&nbsp;</li><li>Strong portfolio showcasing your data visualization skills and experience.&nbsp;</li></ul>

Responsibilities: <ul><li>Involves working closely with industrial partners to evaluate their technical readiness, helping them align with client architectural plays and providing technical direction to develop new solutions and services offerings</li><li>Collaborate with partners to help them build IoT solutions aligned with our client strategy.</li><li>Provide strategic feedback on technology trends and develop business plans for partner enablement.</li><li>Lead partner training initiatives and assist in positioning our client solutions effectively.</li><li>Work cross-functionally with internal teams to adapt or create solutions addressing partner needs.</li><li>Create and deliver compelling solution demonstrations and prototypes</li><li>Provide feedback to product and engineering teams to improve IoT SDKs, APIs, and documentation.</li></ul> Requirements: Industry &amp; Partner Experience: <ul><li>Experience working with partner companies or Gold/Select resellers</li><li>Exposure to automation environments, particularly with Rockwell Automation, Honeywell, or other industrial control vendors</li><li>Familiarity with the integration of OT (Operational Technology) and IT networks</li></ul> Technical Expertise: <ul><li>Strong hands-on knowledge of networking technologies (routing, switching, wireless, security)</li><li>Understanding of security solutions (e.g., ASA/FTD Firewalls, ISE, Umbrella, Duo, etc.)</li><li>Knowledge of network design and architecture in industrial or enterprise environments</li><li>(Optional) Experience with cloud networking (Meraki, SD-WAN, Azure, AWS, etc.)</li></ul> Presales &amp; Commercial Skills: <ul><li>Experience in a presales or customer-facing technical role</li><li>Ability to design and architect solutions based on customer requirements</li><li>Skilled at creating technical proposals, BoMs, solution documentation, and presenting to clients</li><li>Strong communication skills to interface with both technical and business stakeholders</li><li>Familiarity with commercial engagement models (SOWs, pricing, licensing)</li><li>Certifications (Preferred but not mandatory)</li><li>Certifications: CCNP, CCIE (preferred), or other relevant certifications</li><li>Industrial certifications: Rockwell Certified Network Engineer (RCNE), Honeywell Network Specialist, etc.</li><li>Cloud certifications (AWS/Azure/Meraki) – optional</li></ul>

Responsibilities: Agentic AI Development:&nbsp;&nbsp; <ul><li>Design, build, and deploy agentic AI systems using frameworks such as LangChain, Lang Graph, and related libraries.&nbsp;&nbsp;</li><li>Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.&nbsp;</li></ul> RAG Pipelines:&nbsp; <ul><li>Implement and optimize retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.&nbsp;</li></ul> LLM Engineering:&nbsp; <ul><li>Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.&nbsp;</li><li>Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.&nbsp;</li></ul> Enterprise AI Platform:&nbsp; <ul><li>Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.&nbsp;</li><li>Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.&nbsp;</li></ul> MLOps &amp; Observability:&nbsp; <ul><li>Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.&nbsp;</li><li>Applied AI Prototyping:&nbsp;</li></ul> Rapidly prototype, experiment, and iterate to improve AI agent capabilities.&nbsp; Collaboration &amp; Research:&nbsp; <ul><li>Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.&nbsp;</li><li>Collaborate effectively with other engineers, researchers, and data scientists.&nbsp;</li><li>Contribute to the documentation and standardization of technical code and practices.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.&nbsp;</li><li>5+ years overall experience in software development, data science, or machine learning.&nbsp;</li><li>1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.&nbsp;</li><li>1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.&nbsp;</li></ul>

Responsibilities: <ul><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools</li><li>Lead the design and development of solutions using Agentic AI</li></ul> Requirements: Basic Qualifications: <ul><li>Bachelor’s or Master’s in Computer Science, Mathematics, Statistics, or a related field.</li><li>8+ years of experience in software engineering, data science, AI, or a related field.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS.</li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Strong problem-solving skills and the ability to work independently as well as part of a team.</li></ul> Preferred Qualifications: <ul><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Familiarity with Agile development.</li><li>Experience in applications on sales, marketing, and market research.</li><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support.</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI.</li></ul>

Role Description: <ul><li>Executes complex simulations in CFD and Thermal to optimize design and manufacturing.</li><li>Develops complex Multiphysics simulation methods that meets design requirements in thermal management of Electronic Systems, especially in high-speed transceivers, connectors, and their assemblies.</li></ul> Responsibilities: <ul><li>Leading the development and implementation of complex Thermal simulation models to optimize manufacturing, designs or processes.</li><li>Perform calculation &amp; simulation on temperature distribution over system.</li><li>Conducted thermo-mechanical and structural simulations to support design optimization, material selection, and validation from concept to production.</li><li>Proficient in simplifying complex CAD geometries for efficient structural and thermal simulation analyses</li><li>In-depth knowledge of mechanical design, conductive, convective, &amp; radiation heat transfer, and fluid flow mechanics.</li><li>Collaborate with designer, manufacturing, and testing teams to correlate CFD &amp; Thermal Simulation results with physical testing</li><li>Experience with DOE (Design of Experiments) and optimization techniques.</li></ul> Requirements: <ul><li>BE/ B.Tech (Mechanical)</li><li>M Tech (Mechanical) (preferred)/ PHD</li><li>Knowledge of products, design processes and methodology.</li><li>Proficiency in state-of-the-art&nbsp;</li><li>Proficiency in use of MS Office tools.</li><li>Knowledge of associated manufacturing processes (molding, stamping, plating, crimping &amp; assy).</li><li>Knowledge about the Soldering, crimping &amp; welding technologies.</li><li>Knowledge on technical paper publications &amp; applying for patents.</li><li>8- 12 years of industry experience.</li><li>Expertise in Ansys Workbench.</li><li>Experience on connector products (Plastic and Sheet Metal parts).</li><li>Knowledge on material science (Metals, Resins &amp; hyper elastic material) and implement for simulation.</li><li>Correlation of Test and simulation data / results.</li><li>Expertise on CAE tools, Optimization techniques, and testing methods.</li><li>Implementing of LEAN / 6 Sigma / Kaizen techniques to live projects.</li></ul>

Responsibilities: <ul><li>You will be responsible for driving companys growth across the Webex Customer Experience portfolio, with a focus on capturing significant market share in CCaaS, On-Premises Contact Centre, and CPaaS segments.</li><li>Your mission will be to implement high-impact strategies that accelerate adoption and revenue in these rapidly evolving markets.</li><li>The Customer Engagement space is one of the most dynamic and high-growth areas within company.</li><li>The proliferation of smartphones, digital messaging platforms, and the rise of Agentic AI have fundamentally reshaped customer expectations, demanding faster, smarter, and more personalised engagement from businesses.</li><li>As a Customer Engagement Expert, your deep domain expertise and thought leadership will be instrumental in enabling companys broader sales teams.</li><li>You will play a key role in building customer trust and driving adoption of companys AI-powered Contact Centre solutions, including CCaaS, CPaaS, and On-Premise offerings.</li></ul> In this role, you will work across the following teams to help solve customers’ most complex business problems. <ul><li>Global Contact Centre Sales Acceleration team and leadership</li><li>Collaboration with Product Sales Specialists and Solution Architects</li><li>Account Management Teams</li><li>Channel Partners and third-party Contact Centre Solution Partners</li><li>Product Management across companys Global Contact Centre Business Unit</li></ul> Requirements: <ul><li>Proven expertise in AI, Contact Centre, CCaaS, and CPaaS technologies.</li><li>A strong track record in strategic solution selling within both channel-led and direct go-to-market models.</li><li>The ability to position and sell to business decision-makers, backed by a well-established network of senior executive relationships.</li><li>You should possess a comprehensive understanding of Customer Experience technologies and the architectural evolution required for customer success.</li><li>You’ll be expected to engage with executive stakeholders and collaborate with companys technical teams to shape technology roadmaps that align with broader account strategies.</li><li>By applying your business acumen and industry insight, you will align companys portfolio with customer challenges and strategic priorities, ultimately driving revenue growth and market share expansion</li><li>You have demonstrated experience/capability in selling and consulting to Customer Experience executives.</li><li>You will maintain an active, hands-on approach with the team, partners, and customers.</li><li>You love what you do and are passionate about technology, enabling frictionless customer experiences and journeys.</li></ul> You have core experiences in the following areas: <ul><li>Technology Leadership: Communicate a clear technology vision and strategy with a compelling value proposition specifically as it relates to Cloud &amp; On Premise Contact Centre and Experience Management</li><li>Extensive sales/consulting leadership experience managing solution and application sales</li><li>Deep understanding of CCaaS, CPaaS, On-premise Contact Centers, and SaaS-based technologies and architectures, including adjacent technologies like Workforce, Quality Management, and AI.</li><li>You are expected to have customer relationships and understand the India market.</li></ul>

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49 saas models Jobs found

Product Pricing Analyst

Manager, Industrial and Employee Relations

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Partner Solutions Engineer - IOT

IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Staff Simulation Engineer - CFD

Account Executive - Architecture

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Product Pricing Analyst

Manager, Industrial and Employee Relations

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Partner Solutions Engineer - IOT

IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Staff Simulation Engineer - CFD

Account Executive - Architecture

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