Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

Principal AWS Network Infrastructure Engineer

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

Software Engineer In Test (SDET)

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

Responsibilities: <ul><li>Leading development of advanced AI Agentic tech.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions..</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high bar for model development.</li></ul> Requirements: <ul><li>3+ years of people management experience.</li><li>7+ years of AI/ML experience.</li><li>Significant experience in managing larger technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li></ul>

Responsibilities: <ul><li>Lead experimentation and model development for AI/ML solutions in legal products.</li><li>Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Proven experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Able to analyze large-scale legal datasets to extract insights and improve model performance.</li></ul>

Responsibilities: <ul><li>Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Strong experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Strong foundation in statistics, modeling, and large-scale text processing.</li></ul>

Responsibilities: Data Infrastructure:&nbsp; <ul><li>Prepares data infrastructure to support the efficient storage and retrieval of data.</li></ul> Data Formats:&nbsp; <ul><li>Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.</li></ul> Data &amp; Analytical Solutions:&nbsp;&nbsp; <ul><li>Develops complex data products and solutions using advanced engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li></ul> Data Pipelines:&nbsp;&nbsp; <ul><li>Develops and maintains streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li></ul> Data Systems:&nbsp;&nbsp; <ul><li>Reviews existing data systems and architectures to identify areas for improvement and optimization.</li></ul> Stakeholder Management: <ul><li>Collaborates with multi-functional data and advanced analytic teams as well as with business teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li></ul> Data Frameworks:&nbsp; <ul><li>Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li></ul> Automated Deployment Pipelines:&nbsp;&nbsp; <ul><li>Develops automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li></ul> Data Modeling:&nbsp;&nbsp; <ul><li>Performs complex data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience.&nbsp;</li><li>Typically reflects 5 years or more of relevant experience.</li></ul>

Responsibilities: Design and Implementation:&nbsp; <ul><li>Architect and deploy scalable, secure, and highly available network infrastructure solutions in AWS</li></ul> Network Management:&nbsp; <ul><li>Manage and optimize AWS networking services such as VPC, Direct Connect, Route 53, CloudWAN, and Transit Gateway</li></ul> Security:&nbsp; <ul><li>Implement and maintain network security best practices, including firewalls, VPNs, and security groups</li></ul> Automation:&nbsp; <ul><li>Develop and maintain automation scripts using tools like Terraform, CloudFormation, and Python</li></ul> Monitoring and Troubleshooting:&nbsp; <ul><li>Monitor network performance and troubleshoot issues to ensure optimal performance and reliability</li></ul> Collaboration:&nbsp; <ul><li>Work with cross-functional teams to support application development and deployment</li></ul> Documentation:&nbsp; <ul><li>Create and maintain detailed network documentation and diagrams</li></ul> Cost Management:&nbsp; <ul><li>Monitor and optimize cloud costs, implementing cost-saving measures where possible</li></ul> Compliance and Governance:&nbsp; <ul><li>Ensure that all cloud network solutions comply with our client standards</li></ul> Performance Tuning:&nbsp; <ul><li>Continuously improve the performance and reliability of network systems</li></ul> Incident Response:&nbsp; <ul><li>Lead incident response efforts for network-related issues and outages</li></ul> Training and Mentorship:&nbsp; <ul><li>Provide training and mentorship to junior network engineers and other team members</li></ul> Innovation/Continuous Learning:&nbsp; <ul><li>Stay updated with the latest cloud networking technologies and propose innovative solutions to improve the infrastructure</li></ul> Business Competencies: <ul><li class="ql-indent-1">Adaptable to work effectively within a variety of situations and with various individuals, groups or independently</li><li class="ql-indent-1">Ability to document and communicate effectively, explaining technical concepts and network initiatives in business terms in both individual and group settings</li><li class="ql-indent-1">Must be tenacious, overcoming obstacles and identifying risks</li><li class="ql-indent-1">Attention to detail will be critical to assist with the successful implementation of initiatives</li></ul> Requirements: <ul><li class="ql-indent-1">10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li class="ql-indent-1">Strong understanding of AWS network infrastructure and service integration, including VPC, IAM, Transit Gateway, and CloudFormation, and how AWS services such as EC2, EKS, RDS, S3, and Lambda operate within those network architectures.</li><li class="ql-indent-1">Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).</li><li class="ql-indent-1">Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).</li></ul> Technical Skills: <ul><li class="ql-indent-1">In-depth knowledge of AWS networking services and best practices, such as VPC, AWS Firewall, Transit Gateway, WAF, Security Groups, CloudWAN, NACLS, Shield Advance, and Direct Connect</li><li class="ql-indent-1">Advanced understanding of networking protocols and services such as BGP, OSPF, TCP/IP, DNS, DHCP, and VPNs</li><li class="ql-indent-1">Proficiency in network security principles and tools</li><li class="ql-indent-1">Skilled in network automation and scripting</li><li class="ql-indent-1">Experience in developing IaC with advanced skills in tools such as Terraform, AWS CloudFormation, and Ansible for automating infrastructure deployment and management</li><li class="ql-indent-1">Familiar with DevOps practices / CI/CD pipelines using tools like Jenkins, GitLab CI, or GitHub Actions to automate testing and deployment</li></ul>&nbsp;

Responsibilities: <ul><li>Lead the design, development, and deployment of machine learning models using Python for applications including process optimization, predictive analytics, demand forecasting, computer vision, and decision support systems</li><li>Network across manufacturing, R&amp;D, commercial, and business functions to identify and collaboratively execute on high-impact challenges solvable through machine learning techniques</li><li>Build production-ready ML solutions within enterprise platforms (Databricks, Azure ML) including model training, endpoint deployment, and monitoring</li><li>Develop and maintain scalable, modular, well-documented code following MLOps best practices including version control, logging/metadata standards, and CI/CD principles</li><li>Lead code reviews, architectural discussions, and knowledge sharing to maintain high quality, production-ready deliverables across the team</li><li>Collaborate with domain experts and stakeholders across a wide variety of domains to understand needs, integrate ML solutions into workflows, and deliver measurable business value</li><li>Communicate complex machine learning methodology, results, and business impact clearly to technical and non-technical audiences through presentations, documentation, and visualizations</li><li>Stay current with advancements in machine learning, and apply them to solve business challenges</li><li>Mentor and provide technical guidance to data scientists, helping to grow the teams capabilities in Hyderabad</li><li>Support ML governance processes including architecture and methodology reviews, risk assessments, and compliance with enterprise standards</li><li>Lead project planning and execution, managing timelines, resources, and stakeholder expectations</li></ul> Requirements: <ul><li>Masters or Ph.D. in a relevant field such as Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a domain-focused field (Engineering, Chemistry, Economics, Finance, etc.)</li><li>5-8+ years of experience in data science, machine learning, or a related field with demonstrated impact</li><li>Strong foundation in statistical and machine learning theory with proven ability to select, apply, and evaluate appropriate techniques for complex, real-world problems</li><li>Extensive hands-on experience building predictive models and deploying them to production environments using Python</li><li>Proficiency with modern ML frameworks (scikit-learn, XGBoost/CatBoost, TensorFlow/PyTorch) and data manipulation libraries (pandas, polars, numpy)</li><li>Experience with solution architecting and design for ML systems</li><li>Hands-on experience with cloud platforms such as Azure and/or Databricks for deploying and managing ML models and solutions</li><li>Experience with version control (Git), collaborative development, and code review processes</li><li>&nbsp;Strong written and oral communication skills with ability to present technical concepts and results to diverse audiences from technical teams to business leadership</li><li>History of project leadership and driving initiatives from conception to production</li><li>Strong problem-solving skills and the ability to work independently as well as lead and mentor team members&nbsp;</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).</li><li>Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.</li><li>Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.</li><li>Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.</li><li>Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).</li><li>Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.</li><li>Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&amp;A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs. Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.</li><li>Designing and maintaining high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring</li><li>Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.</li></ul> Requirements: <ul><li>Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 5+ years’ experience or in lieu of degree, and 7+ years of relevant work experience in, data engineering or related roles in the financial services or regulated analytics domain.</li><li>Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).</li><li>Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.</li><li>Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).</li><li>Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, Why Labs, Prometheus).</li><li>Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.</li><li>Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.</li></ul>

Responsibilities: <ul><li>Framework Development: Contribute to, maintain and enhance the test automation framework by adding new capabilities and improving maintainability.</li><li>Ensure the framework supports scalability, modularity, and cross-platform compatibility.</li><li>Be ready to jump into unknown areas and quickly implement the most suitable solutions.</li><li>Test Script Development: Design, develop, and maintain robust and reusable test automation scripts.</li><li>Work with different application layers: UI, API, database, and possibly mobile or desktop apps. Implement and maintain utilities and test libraries.</li><li>If required support developers with unit tests.</li><li>Test Strategy &amp; Planning: Collaborate with QA leads and developers to define what to automate, when, and how.</li><li>Ensure test automation is integrated in the CI/CD pipeline and supports continuous testing.</li><li>Test Execution &amp; Maintenance: Regularly run automated tests and analyze results. Identify and troubleshoot test failures, escalating issues when needed. Maintain and update existing test cases and CI/CD pipelines as applications evolve.</li><li>Troubleshooting &amp; Debugging: Investigate test failures and identify root causes— whether it’s a test issue, application defect, or environment problem.</li><li>Provide quick and effective fixes or workarounds.</li><li>Collaboration &amp; Mentorship: Collaborate with developers, QA engineers, DevOps, and product owners to ensure alignment on testing objectives.</li><li>Mentor junior team members on automation best practices and tool usage.</li><li>Code Quality &amp; Version Control: Write clean, maintainable, and efficient automation code. Perform code reviews for junior engineers and provide constructive feedback. Ensure adherence to automation coding standards and version control practices.</li><li>Test Data &amp; Environment Handling: Set up or manage basic test data for automated runs. Run tests across different environments and report inconsistencies.</li><li>Documentation: Document automated tests and provide clear test case descriptions.</li><li>Keep test coverage and automation status updated in tracking tools like Jira, TestRail, or similar.</li></ul> Requirements: <ul><li>Experience &amp; Expertise: Excellent coding skill in Python, JavaScript is a plus.</li><li>Proven experience in building test framework, application development and building applications, working with git.</li><li>Solid experience with API automation testing, microservices solutions, setting up CI/CD pipelines in Azure DevOps or similar.</li><li>Great experience with Docker or similar.</li><li>Agile methodology: Experience in working in an Agile environment and comfortable in dynamic settings and requirements.</li><li>You thrive as fast-paced and are an independent contributor with no support required to drive assigned tasks forward with precision and efficiency.</li><li>Communication &amp; Collaboration: Proficient in cross-functional communication with a demonstrated ability to facilitate team communication and knowledge sharing sessions.</li><li>Technical Proficiency: Hands-on experience with latest development tools and processes, DevOps practices and Cloud solutions like Azure, AWS or similar, Robot Framework, Selenium Grid and reporting tools like Grafana, Report Portal or similar.&nbsp;</li><li>Continuous Improvement: Proactively identify areas for automation improvement or technical debt reduction.</li><li>Stay current with industry trends, tools, and emerging practices.</li><li>Educational Background: A Bachelors degree in Computer Science, Engineering, or a related field, or equivalent practical experience.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain scalable software solutions for the eCommerce domain.</li><li>Work as a key member of an agile Scrum team, actively participating in sprint planning, backlog refinement, daily stand-ups, and retrospectives.</li><li>Collaborating closely with development leads to align on technical direction, architecture, and implementation strategies.</li><li>Analyze and solve complex problems across the stack, from front-end interfaces to back-end services and integrations.</li><li>Understand business and technical requirements to create high-quality, maintainable deliverables.</li><li>Participate in code reviews, design discussions, and continuous improvement of engineering practices.</li><li>Ensure high standards of code quality, reliability, and system performance.</li><li>Support incident resolution and platform stability initiatives.</li></ul> Requirements: <ul><li>4+ years of hands-on programming experience in one or more languages such as Java, C#, JavaScript, Python, Spring boot etc.</li><li>Proven ability to learn and adapt quickly to new technologies, frameworks, and platforms.</li><li>Strong understanding of software engineering principles, design patterns, and scalable architecture.</li><li>Solid experience with RESTful APIs, microservices, and modern development tools (Git, CI/CD, etc.).</li><li>Strong analytical, problem-solving, and debugging skills.</li><li>Working knowledge of relational and/or NoSQL databases.</li><li>Familiarity with cloud platforms (Azure, AWS, or GCP) is a plus.</li><li>Prior experience or understanding of eCommerce systems, shopping carts, order management, product catalog, payment integration, etc., is highly desirable.</li><li>Exposure to DevOps practices, automation, and monitoring tools is a plus.</li><li>Excellent communication and collaboration skills, especially in a distributed team setting.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust, scalable, and secure web applications.</li><li>Utilize Object-Oriented design principles and best practices to ensure high-quality software.</li><li>Write clean, efficient, and well-documented code in C# with both .NET Core and .NET Framework.</li><li>Ensure adherence to Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Create and manage CI/CD pipelines using tools like Jenkins, GitLab CI, or Azure DevOps.</li><li>Automate repetitive tasks in the software development lifecycle, including builds, testing, and deployments.</li><li>Configure and maintain infrastructure for CI/CD pipelines, including servers and containerized environments.</li><li>Leverage cloud platforms like AWS, Azure, or GCP for scalable infrastructure and application management.</li><li>Incorporate DevOps principles to foster collaboration between development and operations teams.</li><li>Integrate unit testing frameworks (e.g., NUnit) into pipelines to ensure robust software quality.</li><li>Utilize test-driven development practices to enhance software reliability.</li><li>Work closely with developers, QA engineers, and operations teams to streamline workflows and address feedback.</li><li>Demonstrate strong communication skills to present ideas, solutions, and progress effectively.</li><li>Monitor CI/CD pipeline execution and troubleshoot issues promptly to minimize downtime.</li></ul> Requirements: <ul><li>Demonstrated knowledge of software application development (certifications and experience considered in lieu of a degree).</li><li>6+ years of experience in software development using C# and .NET.</li><li>5+ years of experience in developing .NET applications, including .NET Core and .NET Framework.</li><li>Proven experience in building enterprise-level web applications.</li><li>Strong background in Object-Oriented design and development.</li><li>Advanced JavaScript experience, including closures and prototype inheritance.</li><li>Proficiency in SQL (DDL and DML) and experience managing database structures.</li><li>Solid understanding of Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Demonstrated use and knowledge of design patterns and cloud-native technologies.</li><li>Experience with Agile methodologies and iterative development processes.</li><li>Proficiency in CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline is required.</li></ul> Preferred work experience and skills: <ul><li>Strong proficiency in C#, JavaScript, and scripting languages like Bash, Python, or PowerShell for task automation.</li><li>Expertise in popular CI/CD platforms like Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline.</li><li>Deep understanding of Git and branching strategies for effective code management.</li><li>Familiarity with unit testing frameworks like Unit, JUnit to integrate automated testing into pipelines.</li><li>Knowledge of cloud platforms like AWS, Azure, or GCP for scalable infrastructure management.</li><li>Familiarity with containerized environments (e.g., Docker, Kubernetes) and microservices architecture.</li><li>Exceptional problem-solving and analytical skills.</li><li>Strong communication and collaboration abilities.</li><li>Self-motivated and able to work independently with minimal supervision.</li><li>Detail-oriented with excellent organizational skills.</li></ul>

Skills

Industry

Location

Jobtitle

42 python Jobs found

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

Principal AWS Network Infrastructure Engineer

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

Software Engineer In Test (SDET)

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

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

EMPLOYER

TALENT

COMPANY

Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

JOBS BY INDUSTRY

JOBS BY LOCATIONS

MODEL JOBS

JOBS BY CITY

Skills

Industry

Location

Jobtitle

42 python Jobs found

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

Principal AWS Network Infrastructure Engineer

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

Software Engineer In Test (SDET)

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

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

EMPLOYER

TALENT

COMPANY

Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

JOBS BY INDUSTRY

JOBS BY LOCATIONS

MODEL JOBS

JOBS BY CITY

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