
Senior ML Engineer
AllCloud · București, Municipiul București, Romania · Hybrid
- IT Services & Consulting
- 501–1,000 employees
- Denver, Colorado
Strong hiring record · median 1 days open
Hiring signal
Actively hiring
Posted 2 days ago · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted 2 days ago
- Still listed on the employer's own board
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 seeking a Senior Machine Learning Engineer – AI & GenAI (AWS) to deliver client-facing AI and Generative AI engagements on AWS.
This is a hands-on consulting and delivery role where you will own technical work streams end to end and work directly with client architects, stakeholders, data scientists, ML engineers, and solution architects.
You will contribute across discovery and assessments, proof-of-concepts, AWS Migration Acceleration Program (MAP) engagements, production hardening, and staff augmentation. The role requires strong technical depth, excellent communication, independent decision-making, and the ability to operate effectively in ambiguous, fast-paced environments.
Key Responsibilities
- Design, build, and deploy Generative AI applications on Amazon Bedrock, including RAG, document intelligence, summarisation, classification, and assistant-style solutions.
- Architect and implement agentic and multi-agent systems using Bedrock, AWS Step Functions, Lambda, and related AWS services.
- Build retrieval solutions using embeddings, hybrid keyword/vector search, Amazon OpenSearch, pgvector, relevance tuning, reranking, citation, and grounding.
- Own the Amazon SageMaker lifecycle, including feature engineering, training, tuning, model registry, deployment, MLOps, retraining, drift detection, and CI/CD.
- Build AI evaluation and observability frameworks using golden datasets, LLM-as-judge, regression testing, error taxonomies, tracing, and human-in-the-loop workflows.
- Implement AI guardrails, prompt-injection defences, PII handling, and responsible AI controls for regulated and data-sensitive use cases.
- Build and integrate AI data foundations using S3, Glue, Spark, Redshift, Athena, DMS, Kinesis, and Firehose.
- Design secure, multi-tenant, scalable, and cost-aware AWS architectures using IAM, Lake Formation, VPC, PrivateLink, API Gateway, EKS, ECS, Fargate, and Lambda.
- Define infrastructure as code using AWS CDK, CloudFormation, or Terraform and deliver through CI/CD.
- Estimate, monitor, and optimise AI and data workload costs, including model selection, token economics, caching, compute, and storage.
- Lead technical discovery, requirements sessions, architecture discussions, client presentations, and executive readouts.
- Contribute through code reviews, reusable accelerators, internal engineering patterns, and mentoring of engineers.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, a related quantitative field, or equivalent demonstrated experience.
- 5–8+ years of experience in machine learning engineering, data science, or AI engineering, including at least 3 years of hands-on AWS experience.
- At least 1 year of production-grade Generative AI/LLM experience, including a system taken to production or a client-accepted POC that you can explain in architectural detail.
- Demonstrated experience working directly with external clients or business stakeholders and independently leading technical sessions.
- Experience working effectively across significant time-zone differences with strong self-direction and ownership.
- Excellent written and spoken English, with the ability to create clear architecture documentation and present to senior audiences.
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. We offer competitive salaries, bonus incentives, benefits, flexible hours, and mentoring. Apply now to become part of the team.
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.
Skills
- Machine Learning
- AWS
- Salesforce
- Generative AI
- Bedrock
- Retrieval-Augmented Generation
- AWS Step Functions
- AWS Lambda
- Embeddings
- OpenSearch
- pgvector
- SageMaker
- MLOps
- LLM
- S3
- AWS Glue
- Spark
- Redshift
- Athena
- AWS Kinesis
- Kinesis Firehose
- IAM
- VPC
- API Gateway
- EKS
- ECS
- AWS Fargate
- AWS CDK
- AWS CloudFormation
- Terraform
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