AIML Engineer

• 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., Sager Electronics is looking for a Power Sales Engineer (PSE) to drive growth within the assigned region by expanding existing customer relationships and developing new business op…
• 2 hours ago

• 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 Role Descriptions: RESPONSITIBLIES1.Model Development DeploymentoDesign| develop| and deploy machine learning models and algorithms into production environments

1. Apply deep learning technologies for tasks such as computer vision

   NLP

   NLU

   ASR

   and semantic understanding.

2. AI Frameworks ToolsoWork with agentic AI frameworks like LangChain and LangGraph. oOptimize and quantize GenAI models| including those using RAG| Transformers| and VectorDBs3.Data Engineering AnalysisoHandle large-scale training and inference using platforms like Databricks and PySpark. oPerform statistical analysis| feature engineering| and dimensionality reduction (e.g.| PCA| SVD| UMAP| t-SNE). 4.Software Engineering IntegrationoBuild scalable AI platforms and integrate ML solutions into existing systems using REST APIs| Docker| and cloud services (Azure| AWS). oCollaborate with cross-functional teams to align AI architecture with business goals. 5.AI Governance StrategyoParticipate in AI governance processes including intake| proof-of-concept| and capital planningoBreak down large initiatives into manageable| cost-effective projects with clear KPIs. 6.Mentorship CollaborationoMentor junior AIML engineers and foster a collaborative| feedback-driven team cultureoEngage in code reviews| pair programming| and community-based education initiatives Essential Skills: AIML Engineer

• 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

• $70,460-117,065 per year