—
Job Description: Position: Machine Learning Engineer Location: Remote / Hybrid Employment Type: Full-time Responsibilities Design, train, and deploy machine learning models for production environments. Build data pipelines for model training, evaluation, and optimization. Work with large-scale datasets, perform feature engineering, data cleaning, and model tuning. Develop scalable algorithms for NLP, computer vision, or recommendation systems. Collaborate with product and engineering teams to integrate ML solutions. Monitor model performance and ensure reliability, accuracy, and efficiency. Document ML workflows, research findings, and technical guidelines. Requirements: Requirements Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related discipline. Strong foundation in machine learning, statistics, and applied mathematics. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/K8s). Knowledge of MLOps best practices is a strong plus. Excellent problem-solving and analytical skills. Benefits: Skills: Ability To Work Under Pressure, Big Picture Thinking, Electro-Mechanical Products
| Skill | Source | Confidence |
|---|---|---|
| Python | llm_hard |
100%
|
| Docker | llm_hard |
100%
|
| Kubernetes | llm_hard |
100%
|
| Data Cleaning | llm_hard |
100%
|
| TensorFlow | llm_hard |
100%
|
| PyTorch | llm_hard |
100%
|
| Scikit-learn | llm_hard |
100%
|
| Feature Engineering | llm_hard |
100%
|
| NLP | llm_hard |
80%
|
| Computer Vision | llm_hard |
80%
|
| MLOps | llm_hard |
80%
|
| AWS (SageMaker, EC2, S3) | llm_hard |
80%
|
| Azure ML | llm_hard |
80%
|
| Google Cloud AI | llm_hard |
80%
|
| Skill | Source | Confidence |
|---|---|---|
| Documentation | llm_soft |
100%
|
| Problem-Solving | llm_soft |
100%
|
| Analytical Thinking | llm_soft |
100%
|
| Query | Country | Status | Response ms | Created |
|---|---|---|---|---|
| Machine Learning Engineer => Relocate to China | extracted | 4509 | 2026-03-22 02:32 | |
| Machine Learning Engineer => Relocate to China | classified | 411 | 2026-03-21 21:02 | |
| junior deep learning engineer in London | gb | duplicate | 8628 | 2026-03-21 17:11 |
| junior machine learning engineer in London | gb | processed | 9822 | 2026-03-21 16:57 |
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"job_description": "Job Description:\nPosition: Machine Learning Engineer\n\nLocation: Remote / Hybrid\nEmployment Type: Full-time\n\nResponsibilities\n\nDesign, train, and deploy machine learning models for production environments.\n\nBuild data pipelines for model training, evaluation, and optimization.\n\nWork with large-scale datasets, perform feature engineering, data cleaning, and model tuning.\n\nDevelop scalable algorithms for NLP, computer vision, or recommendation systems.\n\nCollaborate with product and engineering teams to integrate ML solutions.\n\nMonitor model performance and ensure reliability, accuracy, and efficiency.\n\nDocument ML workflows, research findings, and technical guidelines.\n\nRequirements:\nRequirements\n\nBachelor’s or Master’s degree in Computer Science, AI, Data Science, or related discipline.\n\nStrong foundation in machine learning, statistics, and applied mathematics.\n\nProficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).\n\nExperience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/K8s).\n\nKnowledge of MLOps best practices is a strong plus.\n\nExcellent problem-solving and analytical skills.\nBenefits:\n\nSkills:\nAbility To Work Under Pressure, Big Picture Thinking, Electro-Mechanical Products",
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