AI/ML developer
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Role details
Tech stack
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Job description
Translate data science prototypes into production-grade ML services and pipelines.
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Build training and inference code with reproducibility, versioning, and automated testing.
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Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
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Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
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Collaborate with Data Engineering on feature pipelines and data contracts.
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Own production health: drift detection, performance regression, rollback strategies, and incident response.
Requirements
Artificial Intelligence (AI), Artificial Intelligence (AI), Data Science, Prototyping, Automation, Machine Tool, Incident Response, Software Engineering, Python Programming/Scripting Language, Application Programming Interface (API), 5+ years software engineering with 2+ years shipping ML models to production.
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Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
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Experience with containers and orchestration (Docker/Kubernetes) and API development.
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Understanding of ML system design (data leakage, training-serving skew, drift).
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CI/CD and DevOps practices applied to ML workloads (MLOps).
Preferred / Nice to Have
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Experience with feature stores, model registries, and model monitoring stacks.
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GPU optimization and distributed training experience.
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Experience with responsible AI toolkits and compliance requirements.
Core Skills (from POD sheet)
Python, TensorFlow, PyTorch, Docker, REST APIs
Role Descriptions: RoleAIML EngineerRequired Skills 3 years of experience applying NLP (transformers| gpt| etc) in a production setting using large amounts of data 2-3 years of experience applying LLMs (RAG| vector db| embeddings) to solve real world problems 2-3 years of experience in Python using common data science libraries such as scikit-learn and Databricks Experience applying data science techniques in a commercial enterprise| including supervised| unsupervised learning| NLP| time-series forecasting and other statistical analyses Experience building APIs for the models Strong written verbal communication skills including the ability to present detailed analyses to a broad audience Organized self-starter| with drive and commitment able to work with little supervision Strong analytical| quantitative| problem-solving| and critical thinking skills Experience using vision and speech models in GenAI Essential Skills: RoleAIML EngineerRequired Skills 3 years of experience applying NLP (transformers| gpt| etc) in a production setting using large amounts of data 2-3 years of experience applying LLMs (RAG| vector db| embeddings) to solve real world problems 2-3 years of experience in Python using common data science libraries such as scikit-learn and Databricks Experience applying data science techniques in a commercial enterprise| including supervised| unsupervised learning| NLP| time-series forecasting and other statistical analyses Experience building APIs for the models Strong written verbal communication skills including the ability to present detailed analyses to a broad audience Organized self-starter| with drive and commitment able to work with little supervision Strong analytical| quantitative| problem-solving| and critical thinking skills Experience using vision and speech models in GenAI Desirable Skills: Keyword: Skills: Digital : Machine Learning~Digital : Natural Language Processing (NLP)~AI & Gen AI - Products & Tools Experience Required: 4-6
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