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Senior Software Engineer- Machine Learning

Rol remoto de Machine Learning Engineering con fit claro de ubicación del candidato.

Publicado18 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

50% Delivery and Execution - Develops, tests, deploys, and maintains software, with a clear understanding of the value the software is to provide; Takes on new opportunities and tough challenges with a sense of urgency, high energy and enthusiasm; Consistently achieves results, even under tough circumstances; Develops test suites (functional, destructive, etc) to enable success, rapid deployment of code to production; Takes a broad view when approaching issues; using a global lens
20% Learns and Grows - Learns through successful and failed experiment when tackling new problems; Actively seeks ways to grow and be challenged using both formal and informal development channels
20% Plans and Aligns - Collaborates with other team members in agile processes; Creates new and better ways for the organization to be successful; Works the Product Team to ensure user stories are valuable, developer ready, easy to understand and testable; Delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences; Adapts approach and demeanor in real time to match the shifting demands of different situations; Relates openly and comfortably with diverse groups of people
10% Supports and Enables - Helps grow junior engineers by providing guidance on modern software development frameworks, and leading technical discussions

Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

3-5 years of experience
Languages — Strong in at least one of: Java, Scala, Python
Microservices — REST APIs, gRPC, event-driven architecture (Pub/Sub, Cloud Tasks)
System Design — Distributed systems, scalability, fault tolerance, API gateway patterns
GCP Core — Compute Engine, GKE, Cloud Run, Cloud Functions, IAM
BigQuery — Advanced SQL, partitioning, clustering, cost optimization
Pipelines — Dataflow (Apache Beam), Dataproc (Spark), batch and streaming
Storage — Bigtable, Cloud Storage, Firestore
Orchestration — Cloud Composer (Airflow), Workflows
Vertex AI — Model training, hyperparameter tuning, pipelines, model registry
Frameworks — TensorFlow, PyTorch, scikit-learn MLOps — Model serving (Vertex AI Endpoints), monitoring, retraining pipelines Feature Store — Vertex AI Feature Store Search ML — Ranking, relevance tuning, embeddings (nice to have) AI & LLM Gemini — Gemini API, Gemini Pro, multimodal usage Vertex AI
Generative AI — Model Garden, grounding, tuning RAG — Retrieval Augmented Generation, Vector Search (Vertex AI Vector Search) Agentic AI — Multi-agent frameworks, tool use, autonomous workflows

The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.