Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

 IIAD / SAD / LAD Artificial Intelligence Engineer

Operations Manager

Senior AI Engineer

HR Manager

Lead Scrum Manager

Manager – ADL GMP

Senior UX Designer

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: 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: EH&amp;S (Environment, Health &amp; Safety): <ul><li>Promote a culture of safety across the organization.</li><li>Ensure personnel adhere to established safety guidelines, procedures, and policies.</li><li>Implement lessons learned from security incidents at other facilities to maintain a safe environment.</li></ul> Quality: <ul><li>Promote a culture of quality throughout operations.</li><li>Ensure the operations team follows procedures in their respective areas.</li><li>Support audits from clients and regulatory entities.</li><li>Ensure compliance with Good Manufacturing Practices (GMP) and Good Documentation Practices (GDP).</li></ul> Production: <ul><li>Foster a respectful, dynamic, and challenging work environment.</li><li>Ensure the fulfillment of internal and external operational goals.</li><li>Uphold ethical and regulatory standards in all team behavior.</li><li>Develop and maintain a 5S culture to support efficient operations.</li></ul> Requirements: Competencies &amp; Skills: Core Competencies: <ul><li>Technical Learning: Demonstrated understanding and experience in intensive manufacturing processes.</li><li>Problem Solving: Subject Matter Expert (SME) in complex problem-solving; able to guide teams through solution analysis.</li><li>Ethics and Values: Uphold company values consistently, rewarding alignment and addressing deviations.</li><li>Action Oriented: Energetic and proactive in addressing operational challenges.</li></ul> Job-Specific Knowledge, Skills, and Abilities: <ul><li>Advanced computer skills (Microsoft Word, Excel, etc.).</li><li>Assertive communication and interpersonal skills.</li><li>Strong planning, organizational, implementation, and monitoring skills to ensure Gantt chart and goal achievement.</li><li>Blueprint interpretation and reading.</li><li>Ability to work effectively under pressure.</li><li>Delegation skills while maintaining accountability for results.</li><li>Customer service orientation.</li><li>Effective time management.</li><li>Knowledge of ISO 9002 and FDA-regulated manufacturing environments.</li><li>Experience promoting continuous improvement projects.</li></ul> Experience &amp; Educational Requirements: Experience: <ul><li>Managerial experience in operations/production.</li><li>Minimum 4 years as a senior supervisor, superintendent, or equivalent role in operations/production.</li><li>Approximately 60% office work and 40% time on manufacturing lines (36 months minimum).</li></ul> Education: <ul><li>Engineering degree or equivalent.</li><li>Master’s degree is desirable.</li></ul> Professional Training &amp; Certifications: <ul><li>Six Sigma Green Belt (preferred).</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>

Responsibilities: <ul><li>Lead the HR function at the site to support business objectives and compliance with HR best practices.</li><li>Serve as a trusted advisor to site leadership on workforce planning, employee relations, and organizational development.</li><li>Partner with corporate HR, Quality, EHS, and Operations to align policies, procedures, and culture-building initiatives.</li><li>Initiate and nurture a positive employee relations environment through coaching, communication, and conflict resolution.</li><li>Ensure compliance with federal, state, and local labor laws, as well as cGMP and safety-related employee policies.</li><li>Maintain accurate and confidential employee records, including training and medical surveillance, in cooperation with the EHS Lead.</li><li>Develop, implement, and manage the Learning Management System (LMS) for GMP and technical training.</li><li>Implement employee engagement strategies to nurture a culture of integrity, teamwork, and compliance.</li><li>Administer compensation and benefits programs, including health, retirement, and wellness plans</li><li>Manage payroll coordination with Finance team.</li><li>Monitor and report on key HR metrics (e.g. headcount, turnover, training compliance, absenteeism, engagement)</li><li>Lead the annual organizational review and individual development program.</li></ul> Key Stakeholders: Internal: <ul><li>Site Leadership Team (Operations, Quality, Engineering, Warehouse, Finance, EHS)</li><li>Corporate HR</li><li>Manufacturing and Technical Services Teams</li><li>Validation and Project Management Teams</li></ul> External: <ul><li>FDA and other regulatory agencies</li><li>Third-party auditors and certifying bodies</li><li>External HR service providers</li><li>Customers and business partners</li></ul> Requirements: <ul><li>Bachelor’s degree in human resources, Business Administration, or related field (Master’s or HR certification preferred).</li><li>Minimum 5–10 years of progressive HR experience, including at least 3 years in a manufacturing or GMP-regulated environment and 3 years on site leadership team (pharma, biotech, or medical device strongly preferred).</li><li>Experience supporting high-growth or startup operations is highly desirable.</li></ul> Skills / Competencies: <ul><li>Strong understanding of HR compliance, labor laws, and best practices.</li><li>Demonstrated ability to build HR systems, processes, and policies from the ground up.</li><li>Demonstrated ability to improve HR systems and drive improved engagement and performance.</li><li>Excellent interpersonal, communication, and problem-solving skills.</li><li>Comfortable working in a fast-paced, evolving environment where agility and adaptability are key.</li><li>Strong leadership presence with demonstrated ability to build high-performing teams and compliance culture.</li><li>Effective communication, collaboration, and influencing skills across multiple stakeholders.</li></ul>

Responsibilities: <ul><li>Understands Agile and relevant frameworks (e.g., scrum) to maximize the success of the squad.&nbsp;</li><li>Possess a comprehensive understanding of Agile tools, techniques, principles and values and apply this knowledge to the squad.&nbsp;</li><li>Coach PO and squad to maintain a healthy and prioritized backlog with refined user stories.&nbsp;</li><li>Successfully balance delivery timeframes and continuous iteration so that customer feedback is always incorporated.&nbsp;</li><li>Participate in Scrum of Scrums sessions to ensure the Squad and the others in the Tribe are aligned on priorities, dependencies, and timelines.&nbsp;</li><li>Create a safe environment for all ceremonies to encourage active participation from all squad members.&nbsp;</li><li>Facilitate and mediate conflicts within the squad and Reporting&nbsp;</li><li>Ensure accurate and transparent communications to stakeholders with concise metrics and updates on progress, risks, and impediments.&nbsp;</li><li>Supports Product Owner on release planning.&nbsp;</li><li>Coordinate movement of code between Development, Testing, UAT and Production environments and a related planning, resourcing, and scheduling activities.&nbsp;</li><li>Managing and delivering projects to specifications using a defined development process and delivering within budget and timeline.&nbsp;</li><li>Build meaningful relationships with squad members and resolve most issues leveraging your rapport and trust with squad members.&nbsp;</li><li>Accept change and use it to drive continuous learning and process improvements within the squads.&nbsp;</li><li>Continuously seek and act on feedback received to bring about positive changes. Servant Leadership&nbsp;</li><li>Understand both the squad’s overall capacity and impediments that impact individual members of the squad. Work to create a team culture that values sustainable execution by not over-committing.&nbsp;</li><li>Coach the squad to provide input for squad level decision making to achieve a common goal.&nbsp;</li><li>Identify and work to resolve mindset impediments as they arise.&nbsp;</li></ul> Requirements:﻿ <ul><li>6+ years of experience as a Scrum Master.</li><li>Previous software development lifecycle experience.</li><li>Familiarity with diverse technologies and platforms.&nbsp;</li><li>Familiarity with Agile techniques and tools - Scrum, Kanban, Jira, etc</li></ul>

Role Description: <ul><li>The Manager –ADL, GM P is responsible for leading analytical development activities within a GMP-regulated environment, ensuring robust method development, validation, and transfer for pharmaceutical products.</li><li>This role plays a critical part in supporting product development, regulatory submissions, and commercial manufacturing by providing accurate and compliant analytical data.</li></ul> Responsibilities <ul><li>Lead and manage a team involved in method validation, method transfer, and postproduction studies (Freeze Thaw analysis, Photostability studies, Dilution studies, RLD Characterization, etc.) for 505b(2) and generic ANDAs.</li><li>Troubleshoot and resolve challenges during method validation and method transfer of new products from R&amp;D to manufacturing sites.</li><li>Support regulatory filings and respond to analytical function queries.</li><li>Ensure compliance with cGLP within the ADL GMP function.</li><li>Provide support during quality inspections by regulatory agencies at manufacturing plants.</li><li>Timely closure of LIR, NCR, CCN, CAPA and ensure implementation of corrective and preventive actions.</li><li>Ensure timely compliance with Pharmacopoeia updates.</li><li>Mentor, coach, and develop team members for task execution and personal growth.</li><li>Collaborate with external partners (CRO/CMO) for analytical testing execution.</li><li>Work cross-functionally with project management, regulatory affairs, formulation development, manufacturing, and quality control teams.</li></ul> Requirements: <ul><li>Education: Ph.D. OR MPharm.</li><li>Experience: 3–4 years of team handling experience.</li></ul> Skills Required: <ul><li>Strong knowledge of analytical method validation, method transfer, Pharmacopoeia compliance, cGLP, and documentation practices.</li><li>Sound understanding of analytical techniques with good learning agility.</li><li>Excellent technical writing and computer skills for data recording, protocol/report generation, and presentations.</li><li>Strong coordination, relationship management, and ability to work in multicultural teams.</li><li>Effective communication and team management skills.</li><li>Knowledge of latest quality and regulatory requirements.</li><li>Ability to delegate effectively and take autonomous decisions.</li><li>Critical thinking skills for problem-solving and decision making.</li></ul>

Role Description: <ul><li>We are looking for an experienced Senior UX Designer to join our team and help shape intuitive, user-centric products.</li><li>The ideal candidate has a strong understanding of user experience design, design thinking, and usability best practices, combined with hands-on experience creating delightful digital products.</li></ul> Responsibilities: <ul><li>Lead end-to-end UX design for complex projects — from research and ideation to wireframes, high-fidelity designs, and interactive prototypes.</li><li>Conduct user research, interviews, and usability testing to understand user needs, pain points, and behavior.</li><li>Collaborate closely with product managers, engineers, and stakeholders to align design solutions with business goals.</li><li>Translate requirements into design specifications, user flows, site maps, wireframes, and interactive prototypes.</li><li>Maintain and evolve design patterns, style guides, and design systems for consistency across platforms.</li><li>Advocate for user-centric design principles and educate teammates and stakeholders.</li><li>Analyze user feedback and metrics to iterate and optimize the user experience.</li><li>Stay updated with industry trends and best practices in UX/UI design.</li></ul> Requirements: <ul><li>Experience: 5–8 years in UX design for digital products (web, mobile, SaaS platforms).</li><li>Design Tools: Proficiency with tools like Figma, Sketch, Adobe XD, InVision, or similar.</li><li>Research Techniques: Skilled in conducting user interviews, usability testing, and synthesizing findings.</li><li>Information Architecture: Strong ability to structure complex information intuitively.</li><li>Interaction Design: Skilled in creating interactive and responsive interfaces that delight users.</li><li>Communication: Excellent ability to communicate design ideas, rationale, and solutions clearly.</li><li>Collaboration: Experience working in cross-functional, Agile/Scrum environments.</li><li>Analytical Mindset: Ability to use qualitative and quantitative data to drive design decisions.</li><li>Design Systems: Familiarity with design systems and component libraries.</li><li>Prototyping: Skilled in creating low- to high-fidelity prototypes for stakeholder review and user testing.</li></ul>

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35 reinforcement learning Jobs found

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

IIAD / SAD / LAD Artificial Intelligence Engineer

Operations Manager

Senior AI Engineer

HR Manager

Lead Scrum Manager

Manager – ADL GMP

Senior UX Designer

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Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

IIAD / SAD / LAD Artificial Intelligence Engineer

Operations Manager

Senior AI Engineer

HR Manager

Lead Scrum Manager

Manager – ADL GMP

Senior UX Designer

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WhiteCrow is on a mission to connect companies with the best talent across the globe.