Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Staff Engineer - AI/ML

Principal Applied Data Scientist

Senior Data Scientist II

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>

Role Description: <ul><li>As a Staff Engineer, you will play a pivotal role in shaping the future of Gen AI at our client by defining technical strategy, overseeing complex machine learning architectures, and ensuring seamless integration of Gen AI solutions into our platform and applications at scale.</li><li>You will mentor and guide a small engineering team while providing expertise in state-of-the-art AI/ML practices, ensuring a robust production pipeline and the professional management of models.&nbsp;</li></ul> Responsibilities: <ul><li>Help lead the technical strategy and execution for AI projects across the organization.</li><li>Designing, deploying, and managing the lifecycle of AI/ML models, including retraining and monitoring for continuous improvement within our solution.</li><li>Designing and driving Gen AI features on peta-byte scale datasets Driving innovation in NLP and other ML solutions, ensuring alignment with our client business goals. Architecting, developing and overseeing scalable, production-ready AI systems.</li><li>Providing technical mentorship to the AI/ML engineering team, fostering growth and collaboration.</li><li>Conducting in-depth research and staying abreast of advancements in Gen AI and deep learning technologies.</li><li>Collaborating with cross-functional teams, including Product, to evaluate business requirements and determine optimal AI solutions.</li><li>Reviewing code, offering best practices, and ensuring the delivery of high-quality solutions.&nbsp;</li><li>Representing our client technical excellence through publications, presentations, and participation in industry events.</li><li>Opportunity to work on cutting-edge AI projects at scale.</li></ul> Requirements: <ul><li>8+ years experience in managing large-scale datasets and distributed computing environments, with a preference for Google Cloud Platform expertise.</li><li>Java programming experience.</li><li>Experience with integration and deployment of AI/ML into production at scale within a SaaS solution.</li><li>Demonstrates independent thinking, capable of analyzing unique challenges, overcoming technical hurdles and delivering impactful AI solutions.</li><li>Hands-on experience with Generative AI techniques, including RAG pipelines, LLM fine-tuning, prompt engineering, and diffusion models.</li><li>Strong knowledge of generative AI frameworks and tools, such as Hugging Face, LangChain, or OpenAI APIs.</li><li>Experience in developing and scaling Generative AI solutions for NLP, vision, or multimodal tasks.</li><li>Advanced knowledge of modern AI frameworks, such as PyTorch, TensorFlow/Keras, Hugging Face Transformers, and JAX/Flax.</li><li>Expertise in Python, Docker, Kubernetes, and Helm.</li><li>Excellent communication skills, particularly in mentoring, knowledge sharing, and cross-team collaboration.</li><li>Willingness to be in office 3 days per week.</li></ul>

Role Description: <ul><li>Develop and own the data science roadmap that aligns with our client business goals.</li><li>Define success metrics and oversee the entire lifecycle of data initiatives from concept to production deployment.</li><li>Architect, develop, and deploy state-of-the-art machine learning models.</li><li>Champion best practices in model development, validation, and monitoring in production environments.</li><li>Partner with product, engineering, and business teams to translate business requirements into data-driven solutions.</li></ul> Responsibilities: <ul><li>Provide technical leadership and mentor the data science team.</li><li>Provide technical leadership and mentor the data science team.</li><li>Architect and provide production monitoring and support for our client ML services.</li><li>Stay ahead of industry trends by continuously evaluating emerging technologies and methodologies in data science and machine learning.</li><li>Represent our client technical excellence through publications, presentations, and participation in industry events.</li></ul> Requirements: <ul><li>10+ years of professional experience in data science with a proven track record in building and supporting production grade ML systems.</li><li>Must be highly proficient in Python with hands-on experience in machine learning frameworks (e.g., TensorFlow, PyTorch).</li><li>Experience working with large-scale datasets and distributed computing platforms like GCP.</li><li>Strong understanding of ML lifecycle and MLOps practices.</li><li>Experience with monitoring tools like Prometheus, Grafana and logging systems e.g. ELK stack.</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>

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Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Staff Engineer - AI/ML

Principal Applied Data Scientist

Senior Data Scientist II

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Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Staff Engineer - AI/ML

Principal Applied Data Scientist

Senior Data Scientist II

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

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