As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.
AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io
Role Overview
We are looking for a highly skilled and visionary Senior Machine Learning Engineer to lead the architecture, design, and deployment of enterprise-grade AI/ML projects on AWS. In this role, you will take full technical ownership of advanced AI initiatives, leveraging both native managed services (such as Amazon SageMaker and Bedrock) and custom-built GenAI models to deliver transformative predictive insights and automation to our customers.
As a Senior ML Engineer, you will bridge the gap between complex data engineering and state-of-the-art data science. You will drive the design of scalable MLOps architectures, optimize high-volume data pipelines, and act as a trusted technical advisor to our clients. You will work closely with solutions architects, project managers, and data scientists, while also mentoring junior and mid-level engineers to elevate the team's technical capabilities.
Responsibilities
Architect and Lead ML Solutions: Spearhead the end-to-end architecture, development, and production deployment of robust Machine Learning models, including advanced predictive analytics, NLP, and Generative AI/RAG systems.
Enterprise MLOps & Automation: Define, design, and implement enterprise-grade MLOps strategies. Establish CI/CD pipelines for ML, automated model training, monitoring, versioning, and governance at scale.
AWS AI/ML Mastery: Architect innovative solutions leveraging AWS AI/ML managed services (e.g., SageMaker, Bedrock) to accelerate time-to-market while ensuring high performance and cost-efficiency.
Advanced Data Engineering: Lead the design of highly scalable infrastructure for extracting, transforming, and loading (ETL) data from diverse sources to support complex ML feature stores and model training.
Unstructured Data & Vector Search: Architect systems for the optimal ingestion, processing, and semantic retrieval of unstructured data (text, images, documents) using Vector Databases (e.g., OpenSearch, Pinecone) and graph-based reasoning.
Strategic Advisory & Collaboration: Act as a trusted AI advisor to external enterprise customers and internal C-level executives. Translate complex business constraints into scalable ML architectures and guide clients through their AI adoption journey.
Technical Leadership & Mentorship: Mentor mid-level and junior engineers, establish coding and architectural best practices, and foster a culture of continuous learning and innovation within the team.
Requirements
Experience: 5+ years of proven, hands-on experience in a Machine Learning Engineer or highly technical Data Scientist role, with a strong track record of deploying scalable ML models to production environments.
Education: Bachelor’s (Graduate/Master’s highly preferred) degree in Computer Science, Mathematics, Information Systems, or a related quantitative field.
Expert Programming & ML Frameworks: Deep expertise in Python and mastery of modern ML/Deep Learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
GenAI & LLM Expertise: Strong hands-on experience with Generative AI architectures, including LLMs, fine-tuning methodologies, domain-specific prompting, and RAG pipelines.
Cloud Architecture: Extensive practical experience architecting solutions on AWS, with deep knowledge of AWS AI/ML Services (SageMaker, Bedrock) and core data/compute services (EC2, EMR, Redshift).
Big Data Ecosystem: Proven experience designing complex data pipelines using big data and stream processing technologies (Spark, Kafka, Kinesis, Elasticsearch, Hadoop).
Database Mastery: Advanced SQL proficiency, deep understanding of relational and NoSQL databases (MySQL, Postgres, DynamoDB), and experience with data modeling at scale.
Customer Facing Leadership: Demonstrated ability to lead technical workshops, manage stakeholder expectations, and drive complex projects with external enterprise customers.
Languages: Fluency in Hebrew and English is essential.
Certifications (Strongly Preferred)
AWS Certified Machine Learning – Specialty
AWS Certified Solutions Architect – Professional or Associate
Why work for us?
Our team inspires progress in each other and in our customers through our relentless pursuit of excellence; you will work with leaders who promote learning and personal development.
AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, provincial, or local law.
