This is a remote position.
Vertex is looking for Senior ML Engineers who design build and own production-grade machine learning systems end to end.
We are building a curated pool of Senior AI engineers for upcoming roles with partner/ client companies. Selection into the pool is based on experience technical depth and demonstrated production impact.
Responsibilities
- Build and deploy ML models used in live production environments
- Design data pipelines feature engineering workflows and training loops
- Own model evaluation monitoring and performance improvement
- Work closely with engineers and stakeholders to productionize ML
- Ensure models are reliable scalable and maintainable over time
Requirements
Requirements
- Strong experience with Python and ML frameworks
- Proven experience shipping ML models into production
- Solid understanding of data pipelines and system design
- Experience working with real-world noisy datasets
- Ability to own ML systems beyond experimentation
Benefits
For this role its selection into the Vertex Talent pool based on experience technical depth and demonstrated production impact.
- An energised upbeat environment that strongly fosters employee work-life balance.
- A work culture that rewards goal-oriented professionals who enjoy meeting challenges head-on.
- Amazing personal growth experience
- Working with a motivated and talented team.
- More importantly an opportunity to meaningfully contribute to bringing cutting-edge Tech solutions to life.
Required Skills:
Production ML Deployment (CI/CD for ML & Model Serving) Machine Learning Frameworks (PyTorch TensorFlow or JAX) Data Pipeline Engineering (ETL Spark or Airflow) Feature Engineering & Feature Store Management MLOps & Model Monitoring (Drift Detection & Observability) Scalable System Design (Micro services & High-Availability ML) Automated Training & Evaluation Loops Data Cleaning & Preprocessing for Noisy Datasets Performance Optimization (Inference Latency & Resource Efficiency) Backend Software Engineering (Python API Design & Testing)
Required Education:
BSc.
This is a remote position. Vertex is looking for Senior ML Engineers who design build and own production-grade machine learning systems end to end. We are building a curated pool of Senior AI engineers for upcoming roles with partner/ client companies. Selection into the pool is based on experie...
This is a remote position.
Vertex is looking for Senior ML Engineers who design build and own production-grade machine learning systems end to end.
We are building a curated pool of Senior AI engineers for upcoming roles with partner/ client companies. Selection into the pool is based on experience technical depth and demonstrated production impact.
Responsibilities
- Build and deploy ML models used in live production environments
- Design data pipelines feature engineering workflows and training loops
- Own model evaluation monitoring and performance improvement
- Work closely with engineers and stakeholders to productionize ML
- Ensure models are reliable scalable and maintainable over time
Requirements
Requirements
- Strong experience with Python and ML frameworks
- Proven experience shipping ML models into production
- Solid understanding of data pipelines and system design
- Experience working with real-world noisy datasets
- Ability to own ML systems beyond experimentation
Benefits
For this role its selection into the Vertex Talent pool based on experience technical depth and demonstrated production impact.
- An energised upbeat environment that strongly fosters employee work-life balance.
- A work culture that rewards goal-oriented professionals who enjoy meeting challenges head-on.
- Amazing personal growth experience
- Working with a motivated and talented team.
- More importantly an opportunity to meaningfully contribute to bringing cutting-edge Tech solutions to life.
Required Skills:
Production ML Deployment (CI/CD for ML & Model Serving) Machine Learning Frameworks (PyTorch TensorFlow or JAX) Data Pipeline Engineering (ETL Spark or Airflow) Feature Engineering & Feature Store Management MLOps & Model Monitoring (Drift Detection & Observability) Scalable System Design (Micro services & High-Availability ML) Automated Training & Evaluation Loops Data Cleaning & Preprocessing for Noisy Datasets Performance Optimization (Inference Latency & Resource Efficiency) Backend Software Engineering (Python API Design & Testing)
Required Education:
BSc.
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