Senior Machine Learning Engineer

Vertex AITiger Analytics is looking for a skilled and innovative
Machine Learning Engineer
with hands-on experience in
Google Cloud Platform (GCP)
and
Vertex AI
to design, build, and deploy scalable ML solutions. You will play a key role in operationalizing machine learning models and driving the end-to-end ML lifecycle, from data ingestion to model serving and monitoring.Key Responsibilities
Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training.Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment.Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs.Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows.Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms.Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices.Implement model governance, versioning, explainability, and security best practices within Vertex AI.Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.Requirements
Advanced Generative AIAdvanced RAG including Graph based hybrid retrievalMultimodal agentDeep knowledge on ADK, Langchain Agentic FrameworksFine tuning and DistillationPython ExpertiseExpert in Python with strong OOP and functional programming skillsProficient in ML/DL libraries: TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySparkExperience with production-grade code, testing, and performance optimizationGCP Cloud Architecture & ServicesProficiency in GCP services such as:Vertex AIBigQueryCloud StorageCloud RunCloud FunctionsPub/SubDataprocDataflowUnderstanding of IAM, VPCAPI Development & IntegrationDesigns and builds RESTful APIs using FastAPI or FlaskIntegrates ML models into APIs for real-time inferenceImplements authentication, logging, and performance optimizationSystem Design & ScalabilityDesigns end-to-end AI systems with scalability and fault tolerance in mindHands-on experience in developing distributed systems, microservices, and asynchronous processingBenefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
#J-18808-Ljbffr