Job Description
Job DescriptionPay Rate Range: $ 53.03 - 56.81/hr.
Job Description:
Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.
Key Responsibilities:
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.
Required Qualifications
- 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