and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWSLambda, Athena More ❯
L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWSLambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯
3+ years of professional experience (A technical assessment will be required) Experience with Javascript, NodeJS, Express, Mongo Ability to create clean, modern, testable, well-documented code Serverless experience with AWSlambda or Azure functions Advanced English fluency, verbal and written Professional, empathic, team player Problem solver, proactive, go-getter Why Lumenalta is an amazing place to work at More ❯
Proficiency in one or more core data languages and technologies, such as SQL, Scala, Python, R, PySpark, and Elasticsearch. Proven experience designing, building, and maintaining robust data pipelines using AWS, Azure, and/or open-source frameworks including Spark, Beam, and Airflow. Hands-on experience with real-time data streaming technologies (e.g., Kafka, Pub/Sub). Strong background … defining metrics/KPIs and implementing automated quality controls. Ability to design, build, and optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Experience working within Data Lakehouse platforms such as Databricks … Snowflake, and/or Microsoft Fabric is an advantage. Core Competencies Practical understanding of at least one major cloud provider (AWS or Azure). Strong analytical and problem-solving skills with a keen eye for detail and a drive to deliver business value through data. Excellent communication skills, with the ability to convey technical concepts to non-technical audiences. More ❯
Proficiency in one or more core data languages and technologies, such as SQL, Scala, Python, R, PySpark, and Elasticsearch. Proven experience designing, building, and maintaining robust data pipelines using AWS, Azure, and/or open-source frameworks including Spark, Beam, and Airflow. Hands-on experience with real-time data streaming technologies (e.g., Kafka, Pub/Sub). Strong background … defining metrics/KPIs and implementing automated quality controls. Ability to design, build, and optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Experience working within Data Lakehouse platforms such as Databricks … Snowflake, and/or Microsoft Fabric is an advantage. Core Competencies Practical understanding of at least one major cloud provider (AWS or Azure). Strong analytical and problem-solving skills with a keen eye for detail and a drive to deliver business value through data. Excellent communication skills, with the ability to convey technical concepts to non-technical audiences. More ❯
Proficiency in one or more core data languages and technologies, such as SQL, Scala, Python, R, PySpark, and Elasticsearch. Proven experience designing, building, and maintaining robust data pipelines using AWS, Azure, and/or open-source frameworks including Spark, Beam, and Airflow. Hands-on experience with real-time data streaming technologies (e.g., Kafka, Pub/Sub). Strong background … defining metrics/KPIs and implementing automated quality controls. Ability to design, build, and optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Familiarity with Palantir Foundry or Gotham is a significant … working within Data Lakehouse platforms such as Databricks, Snowflake, and/or Microsoft Fabric is strongly preferred. Core Competencies Deep practical understanding of at least one major cloud provider (AWS or Azure). Strong analytical and problem-solving skills with a keen eye for detail and a drive to deliver business value through data. Excellent communication skills, with the More ❯
Proficiency in one or more core data languages and technologies, such as SQL, Scala, Python, R, PySpark, and Elasticsearch. Proven experience designing, building, and maintaining robust data pipelines using AWS, Azure, and/or open-source frameworks including Spark, Beam, and Airflow. Hands-on experience with real-time data streaming technologies (e.g., Kafka, Pub/Sub). Strong background … defining metrics/KPIs and implementing automated quality controls. Ability to design, build, and optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Familiarity with Palantir Foundry or Gotham is a significant … working within Data Lakehouse platforms such as Databricks, Snowflake, and/or Microsoft Fabric is strongly preferred. Core Competencies Deep practical understanding of at least one major cloud provider (AWS or Azure). Strong analytical and problem-solving skills with a keen eye for detail and a drive to deliver business value through data. Excellent communication skills, with the More ❯
