Senior ML Engineer

Job not on LinkedIn

🔥 42 minutes ago

🇲🇰 North Macedonia – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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ITtude

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤝 B2B

💼 Consulting

🎯 Recruiter

B2B • Consulting • Recruitment

ITtude is a synergy-driven team of IT specialists and top-notch recruiters dedicated to pushing the boundaries of technology to deliver innovative IT services and HR solutions. The company focuses on providing highly qualified personnel that meet the demanding needs of employers in a timely manner. Specializing in staffing, consultancy, and extensive IT recruitment, ITtude emphasizes its expertise in both cleared IT personnel with security certifications and non-cleared IT personnel ready to adapt to a fast-paced business environment.

📋 Description

• Handle the production lifecycle of ML systems, including training, packaging, deployment, monitoring, and controlled rollouts • Design, build, and continuously improve training and retraining pipelines covering data ingestion, labeling/QA loops, feature generation, experiment tracking, and reproducibility • Build and improve high-performance inference services and deployment patterns • Drive inference optimization using ONNX/TensorRT, quantization, batching, and GPU/CPU tuning, with measurable latency and cost improvements • Partner with DevOps/SRE to ensure scaling, reliability, incident readiness, observability, and alerting • Own model versioning, CI/CD, and release workflows to ensure reproducibility and safe production delivery • Strengthen data and model monitoring for performance, drift, and quality, and implement feedback loops for continuous improvement • Communicate results and trade-offs to stakeholders, translating technical outcomes into business value • Ensure model quality through rigorous evaluation and production-grade validation aligned with evolving data and business needs

🎯 Requirements

• Master’s, PhD, or equivalent experience in Computer Science, Engineering, Data Science, or a related field, with strong foundations in mathematics, statistics, and ML • 6+ years of experience across ML engineering and MLOps/production ML, or equivalent experience • Proven track record delivering high-impact systems in production • Expertise deploying models to production, including scalable serving patterns, model packaging, inference optimization, observability, and safe rollout strategies • Experience optimizing model performance and efficiency, including latency/throughput tuning, batching, quantization, ONNX/TensorRT, GPU/CPU optimization, memory, and cost tuning • Strong proficiency in Python • Hands-on experience with PyTorch, scikit-learn, ONNX, and TensorRT • Strong understanding of CI/CD for ML, GitLab CI, Docker, and reproducible workflows • Experience with monitoring and reliability, including metrics, logging, tracing, model/data drift, alerting, SLOs, and incident response practices • Experience with Kubernetes, AWS, FastAPI or similar Python serving frameworks, SageMaker, service meshes, feature stores, and model registries