Machine Learning Engineer

AllCloud

. Deliver AI/ML projects on AWS using native services and custom-built models .

Posted 10/12/2026full-timeRemote • RomaniaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in delivering AI/ML projects on AWS, optimizing data flows, and building complex data infrastructures. Proficient in utilizing big data tools and relational databases while ensuring data security and compliance.

Highest-signal resume keywords

AWS Cloud ServicesMachine Learning ModelsBig Data TechnologiesSQL and NoSQL DatabasesData Pipeline Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine Learning EngineeringDeep Learning Neural NetworksPython CodingSQL Query AuthoringData TransformationBig Data Pipeline ArchitectureData StructuresMetadata ManagementAnalytic Skills

Soft Skills

CollaborationCustomer SupportAnalytical Thinking

Tools & Technologies

AWS EC2AWS RDSAWS EMRAWS RedshiftSparkElasticSearchHadoopKafkaKinesisJupyter Notebooks

Industry Keywords

AI/ML AlgorithmsData LakesCompliance RequirementsOperational IssuesData Security

Tech Stack

Tools & technologies

Amazon RedshiftAWSCassandraCloudDynamoDBEC2ElasticSearchHadoopIoTJavaKafkaMySQLNoSQLPostgresPythonRDBMSScalaSparkSQL

About the role

Key responsibilities & impact

Deliver AI/ML projects on AWS using native services and custom-built models
Support cloud migrations
Optimize customers’ databases and data flows
Enrich operational and functional data flows with AI/ML algorithms
Design, build, and operate infrastructure for data extraction, transformation, and loading using SQL, AWS migration, and big data technologies
Optimize cloud RDBMS engines and resolve customer security, performance, and operational issues
Design, build, and operate large, complex data lakes
Optimize ingestion, storage, processing, and retrieval of diverse data types, including near-real-time events, IoT, images, audio, video, and documents
Use Jupyter Notebooks to build and deploy ML models
Leverage AWS AI/ML pre-built solutions
Keep customer data separated and secure to meet compliance and regulatory requirements
Collaborate with solutions architects, project managers, data scientists, executives, product, data, software development, design teams, customers, and internal stakeholders
Support data-related technical issues, data infrastructure, and business needs

Requirements

What you’ll need

3+ years of experience in a Data Scientist/Machine Learning Engineer role
Bachelor's degree in Computer Science, Mathematics, Informatics, Information Systems, or another quantitative field
Experience with big data tools: Spark, ElasticSearch, Hadoop, Kafka, Kinesis
Experience with relational SQL and NoSQL databases, such as MySQL, Postgres, DynamoDB, or Cassandra
Experience with AWS cloud services: EC2, RDS, EMR, Redshift
Experience with functional and scripting languages: Python, Java, Scala
Experience with ML models for classification, scoring, and more
Experience with Deep Learning Neural Networks, including Convolution and NLP
Experience with AWS AI/ML Services
Experience with Python coding
Advanced SQL knowledge and relational database experience, including query authoring
Experience building and optimizing big data pipelines, architectures, and data sets
Strong analytic skills related to unstructured datasets
Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management
Working knowledge of message queuing, stream processing, and highly scalable big data data stores
Experience supporting and working with external customers in a dynamic environment

Benefits

Comp & perks

Learning and personal development opportunities
Work with leaders who promote learning and personal development
Equal Opportunity Employer