Senior Machine Learning Engineer (Production & MLOps Focus)

Blockchain Engineer

Senior Data Engineer

Director, Data Science

Continuous Improvement Analyst

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

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>Collaborate with frontend and backend developers to integrate smart contracts with web3 applications.</li><li>Rigorously review code to uphold standards of quality and functional robustness.</li><li>Maintain and enhance existing smart contracts based on evolving needs.</li><li>Stay ahead of the curve by updating knowledge on cryptographic and blockchain advancements, ensuring potential security threats are preempted and neutralized.</li><li>Work closely with product managers and stakeholders to crystallize technical needs and system architecture.</li><li>Offer your blockchain and smart contract expertise to a diverse team audience, catering to both technical and non-technical members.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, or a related STEM discipline.</li><li>Excellent debugging and troubleshooting skills.</li><li>Strong written and verbal communication skills.</li><li>Self-motivated with the ability to work in a fast-paced, evolving environment.</li><li>Proficient communication skills in Englis</li><li>Strong understanding of blockchain security practices and potential vulnerabilities.</li><li>Proficiency in Hardhat and Foundry.</li><li>Experience with Solidity security testing tools like Slither, Mythril, Echidna</li><li>Practical experience with scripting languages like Javascript or Typescript.</li><li>Ability to craft unit, integration, fork, and invariant tests, ensuring code longevity.</li><li>Demonstrable aptitude for best development practices, data structures, algorithms, and methodologies.</li><li>Demonstrable experience with Solidity.Design, develop, test, and deploy smart contracts.</li></ul>

Responsibilities: <ul><li>Design, develop, test, and deploy smart contracts.</li><li>Collaborate with frontend and backend developers to integrate smart contracts with web3 applications.</li><li>Rigorously review code to uphold standards of quality and functional robustness.</li><li>Maintain and enhance existing smart contracts based on evolving needs.</li><li>Stay ahead of the curve by updating knowledge on cryptographic and blockchain advancements, ensuring potential security threats are preempted and neutralized.</li><li>Work closely with product managers and collaborators to crystallize technical needs and system architecture.</li><li>Offer your blockchain and smart contract expertise to a diverse team audience, catering to both technical and non-technical members.</li><li>Actively address and rectify issues identified in live smart contracts.</li><li>Stay updated with the latest developments in the Blockchain ecosystem and adapt solutions accordingly</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related STEM field and/or equivalent experience.</li><li>Proven experience in blockchain technology and associated smart contract capabilities.</li><li>Minimum of 3 years of experience in Blockchain Development.</li><li>Demonstrable experience with Solidity.</li><li>Strong understanding of blockchain security practices and potential vulnerabilities.</li><li>Proficiency in Hardhat and Foundry.</li><li>Experience with Solidity security testing tools like Slither, Mythril, Echidna</li><li>Practical experience with scripting languages like JavaScript or Typescript.</li><li>Ability to craft unit, integration, fork, and invariant tests, ensuring code longevity.</li><li>Proven aptitude for best development practices, data structures, algorithms, and methodologies.</li><li>Bachelors degree in Computer Science, Engineering, or a related STEM discipline.</li><li>Excellent debugging and fixing skills.</li><li>Strong written and verbal communication skills.</li><li>Self-motivated with the ability to work in a fast-paced, evolving environment.</li><li>Proficient communication skills in English.</li><li>Development background in sectors such as banking, finance, or trading, paired with a comprehensive grasp of financial instruments and systems.</li></ul>

Responsibilities: <ul><li>Develop and implement accurate forecasting models to predict product demand using historical data.</li><li>Leverage time series analysis techniques to generate business insights and drive data-driven decisions.</li><li>Continuously optimize forecasting models to adapt to changing business needs and improve forecast accuracy.</li><li>Apply advanced ML algorithms (e.g., XGBoost, Random Forest, Deep Learning) to solve complex business problems.</li><li>Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and actionable insights.</li><li>Develop and validate machine learning models to support various analytical use cases.</li><li>Design scalable and maintainable data pipelines and architectures to support analytical workflows.</li><li>Ensure high data quality and consistency across multiple data sources.</li><li>Collaborate with engineering teams to implement best practices in data storage, processing, and governance.</li><li>Build and deploy data solutions on Databricks, leveraging its ML and Spark capabilities.</li><li>Utilize AWS services (e.g., S3, EC2, Lambda, SageMaker) for scalable cloud-based model training and deployment.</li><li>Ensure cost-effective and optimized use of cloud resources in project implementations.</li><li>Design end-to-end analytics and ML solutions tailored to client needs.</li><li>Lead technical discussions and contribute to solution architecture.</li><li>Translate business requirements into technical specifications and deliver actionable results.</li><li>Understand key metrics and pain points within manufacturing and supply chain operations.</li><li>Use domain knowledge to frame problems accurately and drive impactful analytical outcomes.</li><li>Collaborate with stakeholders to ensure alignment between analytics and business goals.</li><li>Understand SAP modules related to supply chain and manufacturing (e.g., MM, PP, SD) Use SAP knowledge to enhance data modeling and business context understanding.</li></ul> Requirement: <ul><li>Skills Required: o Strong proficiency in Python o Expertise in Time Series Forecasting and Demand Forecasting o Familiarity with Advanced ML Algorithms and Data Analysis o Must have experience in Data Architecture – practical exposure required o Hands-on experience with Databricks and AWS (should be visible in past projects) o Design and solutioning experience highly valued</li><li>Strong background in data architecture, solution design, and end-to-end ML model lifecycle</li><li>Experience as Data Architect, Solution Architect, or in equivalent architectural roles</li><li>Should come from a product-based or data engineering-focused startup background</li></ul>

Responsibilities: Strategic Leadership:&nbsp; <ul><li>Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li></ul> Team Management:&nbsp; <ul><li>Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li></ul> Advanced Research Direction:&nbsp; <ul><li>Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li></ul> Machine Learning and AI Solutions:&nbsp; <ul><li>Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li></ul> Data Collection and Preparation:&nbsp; <ul><li>Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li></ul> Data Visualization Strategy:&nbsp; <ul><li>Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li></ul> Cross-functional Collaboration:&nbsp; <ul><li>Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li></ul> Model Deployment and MLOps:&nbsp; <ul><li>Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li></ul> Documentation Standards:&nbsp; <ul><li>Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li></ul> Budget and Resource Management:&nbsp; <ul><li>Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li></ul> Ethical AI Governance:&nbsp; <ul><li>Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: Digital Factory Corporate Application Deployment: <ul><li>Responsible for the implementation and deployment of corporate-developed applications within factory settings, ensuring seamless integration and operation.</li><li>Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.</li><li>Continuously improve and optimize the performance of applications based on user feedback and system analytics.</li></ul> Digital Factory Local Application Development: <ul><li>Design, develop, and maintain digital factory applications that improve operational efficiency and support business growth within our manufacturing facilities.</li><li>Collaborate with cross-functional teams to understand and translate business requirements into technical solutions that drive process optimization and innovation.</li></ul> AI Model Development: <ul><li>Seamless collaboration with corporate AI teams to design and develop advanced AI models and tailored to specific business problems or application requirements.</li><li>Conduct research on the latest AI techniques and algorithms to continuously improve the performance and accuracy of existing models.</li></ul> AI Model Deployment and Maintenance: <ul><li>Oversee the deployment of AI models from development environments to production environments, ensuring a smooth transition and minimal disruption to business operations.</li><li>Set up monitoring and alert systems to detect and respond to any issues that may arise during the operation of the AI systems.</li><li>Provide ongoing maintenance and support for deployed AI models, including updating and retraining as needed to adapt to changing business conditions or data characteristics.</li></ul> Collaboration and Communication: <ul><li>Work closely with cross-functional teams including data scientists, software engineers, product managers, and domain experts to define project requirements and deliverables.</li><li>Communicate technical findings and progress to non-technical stakeholders in a clear and understandable manner.</li><li>Participate in team meetings, code reviews, and knowledge sharing sessions to contribute to the overall team development.</li></ul> Requirements: <ul><li>Total experience – 5+ years</li><li>On manufacturing digitalization, IT understandable, know basic of programming, system migration, IT related candidate in manufacturing engineering.</li><li>Cover both plant</li><li>Mandarin Speaking requirements is a must</li><li>Good to come from engineering background</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions</li><li>Lead the development of AI and machine learning models to solve business problems</li><li>Research, build, and deploy models based on shallow and deep machine learning</li><li>Train robust NLP-based models on large datasets</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs</li><li>Design APIs for disseminating data science outputs</li><li>Oversee the scaling of production systems to meet growing demands</li></ul> Requirements: <ul><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><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</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>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have 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></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</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><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

About the Role : <ul><li>As a data scientist on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments.&nbsp;</li><li>You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets including matter and contract repository, invoice/legal spend data and work management.&nbsp;</li><li>You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators.</li><li>You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.</li><li>We are committed to advancing gender diversity within the technology sector and supporting greater representation of women in tech. To further this commitment,</li></ul> Responsibilities: <ul><li>Develop and implement LLM-based applications tailored for legal use-cases&nbsp;</li><li>Evaluate and help maintain our data assets and training/evaluation data sets&nbsp;</li><li>Design and build pipelines for preprocessing, annotating, and managing legal document datasets&nbsp;</li><li>Collaborate with legal experts to understand requirements and ensure ML-applications meet domain-specific needs&nbsp;</li><li>Conduct experiments and evaluate model performance to drive continuous improvements&nbsp;</li><li>Fine-tune and deploy large language models to enhance their performance on legal text processing tasks&nbsp;</li><li>Interface with other technical personnel or team members to finalize requirements.&nbsp;</li><li>Work closely with other development team members to understand complex product requirements and translate them into software designs.&nbsp;</li><li>Successfully implement development processes, coding best practices, and code reviews for production environments.</li></ul> Requirements:&nbsp; <ul><li>Able to work in person 2 days per week&nbsp;</li><li>Bilingual English and Spanish&nbsp;</li><li>Practical experience with large language models, prompt engineering, fine-tuning RAG-based applications and benchmarking, using frameworks such as LangChain&nbsp;</li><li>MS in Data Science, Computer Science, Statistics, Machine Learning, or relevant work experience&nbsp;</li><li>Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, Flair, BERT (ways to vectorize text data)&nbsp;</li><li>Formal training in machine learning: dimensionality reduction, clustering, embeddings, and sequence classification algorithms&nbsp;</li><li>Strong Python background&nbsp;</li><li>Knowledge of AWS, GCP, Azure, or other cloud platform&nbsp;</li><li>Understanding of data modeling principles and complex data models.&nbsp;</li><li>Proficiency with relational and NoSQL databases as well as vector stores (e.g., MySQL, Postgres, Solr, Elasticsearch/OpenSearch)</li><li>Knowledge of Spark-Scala, Ray or other distributed computing systems highly preferred&nbsp;</li><li>Knowledge of API development, containerization, and machine learning deployment highly preferred&nbsp;</li><li>Experience with ML Ops/AI Ops including experiment tracking tools like LangFuse and DVC&nbsp;</li><li>Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers Work in a way that works for you We promote a healthy work/life balance across the organization. </li><li>We offer an appealing working prospect for our people.&nbsp;</li><li>With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate. </li><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.</li></ul>

Responsibilities: <ul><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems. Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units. Overseeing the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units.</li><li>Overseeing the scaling of production systems to meet growing demands.</li></ul> Requirements: <ul><li>Possess an advanced or Masters education in Computer Science, Mathematics, Statistics, or a related field. Have experience working directly with large language models and transformer-based architectures including BERT, RoBERTa, T5 etc.</li><li>Be proficient in working with big data technologies and tools like Hadoop, Spark, or AWS.</li><li>Have experience and knowledge of applying LLMs including ChatGPT, GPT 3.5, Claude, Mistral, etc.</li><li>Be a natural problem solver, able to lead and mentor junior data scientists, and collaborate with cross-functional teams.</li><li>Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forests Possess advanced programming skills in Python, R, or other relevant languages for data analysis.</li></ul>

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13 algorithms Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Blockchain Engineer

Blockchain Engineer

Senior Data Engineer

Director, Data Science

Continuous Improvement Analyst

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

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13 algorithms Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Blockchain Engineer

Blockchain Engineer

Senior Data Engineer

Director, Data Science

Continuous Improvement Analyst

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist II

Senior Data Scientist

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

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