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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # USA_Developer - **Company:** Varite Inc - **Location:** Minnetonka, MN, United States - **Experience:** Experienced - **Salary:** $110,302.0 - $118,165.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automation of Tests, Continuous Integration, Information Engineering, Information Leak Prevention, DevOps, Distributed Computing Environment, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Azure Machine Learning, Software Engineering, Management of Software Versions, Feature Store, Pytorch, Retrieval-Augmented Generation, Large Language Models, Generative AI, Scikit Learn, Kubernetes, Deployment Automation, Data Analytics, Machine Learning Operations, Api Design, Restful APIs, GPT, Docker, Unsupervised Learning, Databricks - **Published:** September 30, 2026 - **Apply:** https://www.careerjet.com/job/us3174f70749236c5d101843a66c8e57a5/eaa ## About the Role 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, 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: Category Name Required Importance Experience SkillCategoryTest1_MN AI & Gen AI - Products & Tools Yes 1 7 years SkillCategoryTest1_MN Digital : Machine Learning Yes 1 7 years SkillCategoryTest1_MN Digital : Natural Language Processing(NLP) Yes 1 7 years ## 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. ## Related Videos - [Livecoding with AI](https://www.wearedevelopers.com/videos/1201-livecoding-with-ai) - [Docker does that? 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