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[Remote] Senior Delivery Consultant - AI/ML, AWS Professional Services
Note: The job is a remote job and is open to candidates in USA. Amazon Web Services (AWS) is a comprehensive cloud platform provider whose Professional Services team helps customers achieve enterprise cloud adoption and business outcomes. The Delivery Consultant will lead customer-focused teams in designing, implementing, and managing AI/ML and Generative AI solutions on AWS, including machine learning pipelines, MLOps, model deployment, and monitoring. The role also provides technical guidance, architecture recommendations, and best practices throughout the ML project lifecycle.
Responsibilities
- Leading project teams and implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring
- Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML worklo
- Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable
- Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models
- Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
- Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts
- Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies
Skills
- • Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
- • Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
- • 5+ years of cloud architecture and solution implementation experience
- • 5+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
- • 5+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with understanding of distributed computing (e.g., data pipelines, training and inference, ML infrastructure design)
- • 5+ years developing predictive modeling, natural language processing, and deep learning, with experience in building and deploying ML models on cloud (e.g., Amazon SageMaker or similar)
- • Experience with the AWS platform, web services, software development, or related technologie
- • Experience conveying complex technical concepts to both technical and business audiences
- • Knowledge of one or more ML Frameworks (e.g., PyTorch, TensorFlow) and ML methods including NLP models (BERT, GPT-2/3), computer vision-based models (object detection, image recognition), and text-based models (Seq2Seq, Topic modeling)
- • Knowledge of security and compliance standards including HIPAA and GDPR
- • Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines
- • Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- • Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions)
- Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Health insurance, including medical, dental, vision, and prescription coverage
- Basic Life & AD&D insurance
- Option for Supplemental life plans
- Employee Assistance Program (EAP)
- Mental Health Support
- Medical Advice Line
- Flexible Spending Accounts
- Adoption and Surrogacy Reimbursement coverage
- 401(k) matching
- Paid time off
- Parental leave
- Flexibility as part of our working culture
- Employee-led and company-sponsored affinity groups
- Inclusion events
- Knowledge-sharing, mentorship and other career-advancing resources
Company Overview
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