Senior ML Ops Engineer

5+ years of experience building and deploying ML systems, especially in NLP or applied ML. Hands-on experience solving end-to-end real-world problems — from data ingestion and modeling to deployment and measurable results. Strong grasp of modern NLP techniques: embeddings, retrieval systems, generative models, prompt engineering, fine-tuning, and...

Must-have:5+ years of overall software engineering experience.At least 1 year as an MLOps or ML Engineer in production environments.Strong Python programming skills, especially in data-heavy contexts.Hands-on experience with ML infrastructure at scale.At least 1 year of data engineering experience.Strong knowledge of the ML lifecycle and...

Do we have a match?As a Senior AI/ML Engineer, you must meet most of the following criteria:Strong grasp of core ML concepts (supervised/unsupervised learning, regularization, etc.). Hands-on experience with various classic ML models (classification, regression, clustering, anomaly detection) and with DL models utilizing various neural network...

Must-have: 5+ years of overall software engineering experience. At least 1 year as an MLOps or ML Engineer in production environments. Strong Python programming skills, especially in data-heavy contexts. Hands-on experience with ML infrastructure at scale. At least 1 year of data engineering experience. Strong knowledge of the ML lifecycle and...

2,5+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML modelsBroad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platformAdvanced proficiency with Python and SQL in version control systems (git) plustheir use in building ML & data...

Do we have a match? As a Senior AI/ML Engineer, you must meet most of the following criteria: Strong grasp of core ML concepts (supervised/unsupervised learning, regularization, etc.). Hands-on experience with various classic ML models (classification, regression, clustering, anomaly detection) and with DL models utilizing various neural network...

5+ years of hands-on DevOps/SRE experience in high-growth SaaS startups. Proven chops with AWS, ECS/EKS, Terraform, GitHub Actions, Jenkins, and modernobservability stacks. Track record of platform engineering that boosts developer productivity and SRE rigorthat keeps SLAs honest. Comfort automating the boring stuff—bash, Python, Groovy, or whatever gets...

2,5+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML models Broad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platform Advanced proficiency with Python and SQL in version control systems (git) plustheir use in building ML & data...

doświadczenie w obszarze uczenia maszynowego, AI lub data science (minimum 2 lata – w zależności od poziomu), biegłość w Pythonie i bibliotekach ML (np. scikit-learn, TensorFlow, PyTorch, Keras, OpenCV), znajomość zasad tworzenia oprogramowania i narzędzi typu Git, CI/CD, Docker, Kubernetes, doświadczenie w pracy z danymi i SQL oraz...

What you’ll need to succeed in this role: 5+ years of commercial experience designing and implementing scalable AI solutions (Machine Learning, Predictive Modeling, Optimization, NLP, Computer Vision, GenAI, LLMs, Deep Learning). Proficiency in developing ML algorithms from scratch to production deployment. Strong programming skills in Python: writing...