Machine Learning Engineer

AllCloud; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

AllCloud seeks a Senior Machine Learning Engineer to own enterprise AI initiatives on AWS. You will architect and deploy ML models, build scalable MLOps, and guide clients through AI adoption. The role requires strong Python, GenAI experience, and leadership across data science and engineering teams.

You will mentor engineers, define best practices, and partner with architects to deliver high-impact predictive analytics and automation for diverse enterprise customers.

Qualifications

• 5+ years hands-on ML engineering or data science with production models.
• Strong Python and modern ML frameworks proficiency.
• Extensive experience with AWS AI/ML services (SageMaker, Bedrock).
• Deep knowledge of data pipelines, MLOps, and CI/CD for ML.
• Expert in NLP, GenAI, LLMs, and RAG workflows.
• Experience designing scalable ML architectures for enterprise customers.
• Fluent in Hebrew and English; excellent stakeholder communication.

Responsibilities

• Architect end-to-end ML solutions, production deployment and monitoring.
• Define MLOps, CI/CD pipelines, model versioning, and governance at scale.
• Leverage SageMaker/Bedrock and custom GenAI models to deliver insights.
• Lead data engineering for scalable feature stores and data pipelines.
• Design vector retrieval with OpenSearch and Pinecone for unstructured data.
• Advise external clients and internal teams; mentor engineers.
• Collaborate with solutions architects and project managers.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Hugging Face

LLMs

RAG

MLOps

CI/CD

SageMaker

Bedrock

OpenSearch

Pinecone

Spark

Kafka

Kinesis

Elasticsearch

Hadoop

SQL

MySQL

PostgreSQL

DynamoDB

NoSQL

Data Modeling

Hebrew

English

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

SageMaker

Bedrock

AWS

OpenSearch

Pinecone

Spark

Kafka

Kinesis

Job description

About AllCloud

AllCloud is a leader in amplifying organizations' cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.

AllCloud is a leader in AI-led professional and managed services. 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.
• 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.