Talent Worx is a growing services & recruitment consulting firm, we are hiring for our client which is a globally leading provider of financial intelligence, data analytics, and AIdriven solutions, empowering businesses worldwide with insights for confident decision making. Join to work on cutting edge technologies, drive digital transformation, and shape the future of global markets.
Requirements
Whats in it for you :
- Be part of a global company and build solutions at enterprise scale
- Lead and grow a technically strong ML engineering function
- Collaborate on and solve high-complexity, high-impact problems
- Shape the engineering roadmap for emerging AI / ML capabilities (including GenAI
integrations)
Key Responsibilities :
Architect, develop, and maintain production-ready data acquisition, transformation, and MLpipelines (batch & streaming)
Serve as a hands-on lead-writing code, conducting reviews, and troubleshooting to extendand operate our data platforms
Apply best practices in data modeling, ETL design, and pipeline orchestration using cloud-native solutions
Establish CI / CD and MLOps workflows for model training, validation, deployment,monitoring, and rollback
Integrate GenAI components-LLM inference endpoints, embedding stores, prompt services-into broader ML systems
Mentor and guide engineers and data scientists; foster a culture of craftsmanship andcontinuous improvement
Collaborate with cross-functional stakeholders (Data Science, Product, IT) to align onrequirements, timelines, and SLAs
What We’re Looking For :
8-12 years' professional software engineering experience with a strong MLOps focusExpert in Python and Apache Spark for large-scale data processingDeep experience deploying and operating ML pipelines on AWS or GCPHands-on proficiency with Docker, Kubernetes, and related container / orchestration toolingSolid understanding of the full ML model lifecycle and CI / CD principlesSkilled in streaming and batch ETL design (e.g., Kafka, Airflow, Dataflow)Strong OOP design patterns, Test-Driven Development, and enterprise system architectureAdvanced SQL skills (big-data variants a plus) and comfort with Linux / bash toolsetsFamiliarity with version control (Git, GitHub, or Azure DevOps) and code review processesExcellent problem-solving, debugging, and performance-tuning abilitiesAbility to communicate technical change clearly to non-technical audiencesNice to have :
Redis, Celery, SQS and Lambda based event driven pipelinesPrior work integrating LLM services (OpenAI, Anthropic, etc.) at scaleExperience with Apache Avro and Apache KafkaFamiliarity with Java and / or .NET Core (C#)