USA_Developer

Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions., Translate data science prototypes into production-grade ML services and pipelines.

• Build training and inference code with reproducibility, versioning, and automated testing.
• Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
• Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
• Collaborate with Data Engineering on feature pipelines and data contracts.
• Own production health: drift detection, performance regression, rollback strategies, and incident response.

5 years software engineering with 2 years shipping ML models to production.

• Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
• Experience with containers and orchestration (Docker/Kubernetes) and API development.
• Understanding of ML system design (data leakage, training-serving skew, drift).
• CI/CD and DevOps practices applied to ML workloads (MLOps).

Preferred / Nice to Have

• Experience with feature stores, model registries, and model monitoring stacks.
• GPU optimization and distributed training experience.
• Experience with responsible AI toolkits and compliance requirements.

Core Skills (from POD sheet) Python, TensorFlow, PyTorch, Docker, REST APIs

Required 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

Skills: Digital : Machine Learning~Digital : Natural Language Processing (NLP)~AI & Gen AI - Products & Tools

Experience Required: 4-6 years

Skills:CategoryNameRequiredImportanceExperienceSkillCategoryTest1_MNAI & Gen AI - Products & ToolsYes1>7 years SkillCategoryTest1_MNDigital : Machine LearningYes1>7 years SkillCategoryTest1_MNDigital : Natural Language Processing(NLP)Yes1>7 years