- Company Name
- Corsearch
- Job Title
- ML Engineer (Production-focused)
- Job Description
-
**Job Title:** ML Engineer (Production-focused)
**Role Summary:**
Build, deploy, and maintain scalable machine‑learning models for large‑scale detection and classification. Own the full ML lifecycle—data processing, training, evaluation, deployment, and monitoring—ensuring fast, stable, and reliable production systems.
**Expectations:**
- Deliver end‑to‑end ML pipelines that meet strict latency, throughput, and reliability targets.
- Demonstrate measurable impact (e.g., precision gains, latency reductions, uptime improvements).
- Collaborate with software engineering teams to integrate models into a microservice architecture and maintain CI/CD workflows.
**Key Responsibilities:**
- Design, train, and optimize PyTorch/TensorFlow models for detection, classification, and automation tasks.
- Convert trained models into production‑ready services (Docker containers, model servers).
- Tune inference performance—latency, memory, and throughput—using profiling and optimization techniques.
- Build and maintain automated ML pipelines: data ingestion, preprocessing, validation, deployment, and monitoring.
- Implement model versioning, testing, and CI/CD pipelines to ensure reproducible releases.
- Monitor model performance in production, trigger retraining or drift mitigation as needed.
- Work with infrastructure teams to deploy models on cloud (AWS) or container orchestration (EKS, Lambda).
**Required Skills:**
- 3+ years as an ML Engineer delivering production models.
- Proficient in Python (production‑grade).
- Hands‑on experience with PyTorch (preferred) or TensorFlow.
- Proven deployment/serving experience (Docker, model servers).
- Strong inference optimization (latency, resource usage).
- Deep understanding of ML pipeline automation and CI/CD.
- Experience with Docker, Kubernetes/containers.
- Fluent in English.
- Availability in CET‑aligned time zone (CET − 2 to CET + 4).
**Nice to Have:**
- AWS services: SageMaker, EKS, Lambda, S3.
- Experience with high‑throughput/ high‑load systems.
- CI/CD tooling for ML.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related technical field (Master’s preferred).