
AI/ML Software Engineer
2 days ago
We are seeking a skilled AI/ML Software Engineer to join our team. As a key member of our engineering team, you will be responsible for designing, developing, and deploying artificial intelligence and machine learning models that drive business growth.
About the Role:- Design and develop end-to-end ML pipelines including data ingestion, feature engineering, model training, hyperparameter tuning, evaluation, registration, and automated promotion.
- Harden research code into production-grade microservices, package models in Docker/Kubernetes, and expose secure REST, gRPC, or event-driven APIs for consumption by downstream applications.
- BUILD and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines, or business-logic layers to deliver insights to users with sub-second latency.
- Optimise performance and cost at scale by selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantisation/pruning, and tuning GPU/CPU auto-scaling policies to meet strict SLA targets.
- Instrument comprehensive observability real-time metrics, distributed tracing, drift & bias detection, and user-behaviour analytics to enable rapid diagnosis and continuous improvement of live models and applications.
- EMBED security and responsible-AI controls (data encryption, access policies, lineage tracking, explainability, and bias monitoring) in partnership with Security, Privacy, and Compliance teams.
- Contribute reusable platform components (feature stores, model registries, experiment-tracking libraries) and evangelise best practices that raise engineering velocity across squads.
- Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
- 6-8 years of experience in AI/ML and enterprise software.
- Comprehensive command of machine-learning algorithms regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers), and modern LLM/RAG techniques with the judgment to choose, tune, and operationalise the right method for a given business problem.
- Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
- Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs, and agent frameworks (e.g., LangChain, Semantic Kernel).
- Proficiency in Python and Java; containerisation (Docker/K8s); cloud (AWS, Azure, or GCP); and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
- Strong business-case skills able to model TCO vs. NPV and present trade-offs to executives.
- Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.
- A competitive salary and benefits package.
- The opportunity to work on challenging projects with a talented team.
- A collaborative and dynamic work environment.
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