Machine Learning Software Engineer (Remote | $80–$140/hr)
- Canada
- Télétravail
- Publié 1 sept. 2026
- 1 poste
80 $ US–140 $ US / heure
- Type d’emploi
- Temps partiel
- Niveau d’expérience
- Expérimenté · 5+ ans
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Niveau d’expérience
- Mid-Senior level
- Mode de candidature
- La candidature directe est offerte
Ce poste est expiré
Ce poste chez Synthires n’accepte plus de candidatures. L’offre originale reste disponible ci-dessous à titre de référence.
Expiré le 12 sept. 2026
Offre d’emploi originale
Design and refine machine learning models and data pipelines using Python and MongoDB to support AI training. Evaluate model performance through benchmarking and optimization to ensure the deployment of next-generation AI systems.
Détails du poste
Machine Learning Engineer Position: Machine Learning Engineer Type: Hourly Contract Compensation: $80–$140/hour Location: Remote About the Opportunity This opportunity is for experienced Machine Learning Engineers with expertise in Python, machine learning, data analysis, model development, and MongoDB to contribute to advanced AI training and evaluation projects. You'll apply your technical expertise to design and refine machine learning solutions, analyze datasets, evaluate model performance, and develop reliable workflows that support the training and deployment of next-generation AI systems. Responsibilities Design, develop, and refine machine learning models using Python and relevant ML frameworks. Analyze and process large datasets for model training, validation, and evaluation. Use MongoDB for efficient data storage, manipulation, querying, and retrieval. Develop and maintain data preprocessing and feature engineering pipelines. Evaluate model performance using appropriate metrics, benchmarking, and validation techniques. Perform hyperparameter tuning and iterative model optimization. Collaborate with cross-functional teams to identify opportunities for model and workflow improvements. Integrate data pipelines into training and inference workflows. Document experiments, methodologies, results, and technical decisions to ensure reproducibility. Provide actionable insights and recommendations based on machine learning and data-driven findings. Required Qualifications Professional experience working as a Machine Learning Engineer, ML Developer, Data Scientist, or similar role. Strong proficiency in Python and machine learning development. Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Practical experience using MongoDB for data management and retrieval. Strong understanding of machine learning algorithms, model evaluation, and data preprocessing. Experience with feature engineering, hyperparameter tuning, and model benchmarking. Strong analytical and problem-solving abilities. Excellent written communication and technical documentation skills. Ability to work independently and collaborate effectively in a remote environment. Preferred Qualifications Experience deploying or operationalizing machine learning models in cloud or enterprise environments. Familiarity with ML pipelines, model serving, and inference workflows. Experience working with large-scale datasets and production ML systems. Knowledge of MLOps, model monitoring, or automated ML workflows. Experience contributing to AI training, model evaluation, or data-quality initiatives. Strong understanding of scalable data and machine learning architectures. Ability to adapt quickly to evolving technical requirements and project priorities. Compensation Competitive compensation of $80–$140/hour. Hourly contract engagement. Fully remote with flexible working arrangements. Opportunity to contribute to next-generation AI training and evaluation projects. Application Process Easy Apply on LinkedIn Check Email for Next Steps Complete the required assessment based on your professional background Participate in the interview/evaluation stage Hiring team review
Ce que vous ferez
Design and refine machine learning models and data pipelines using Python and MongoDB to support AI training. Evaluate model performance through benchmarking and optimization to ensure the deployment of next-generation AI systems.
Exigences
Requires professional experience as an ML Engineer or Data Scientist with strong proficiency in Python and frameworks like TensorFlow or PyTorch. Practical experience with MongoDB and a deep understanding of ML algorithms and data preprocessing are essential.
Compétences indiquées
- Technical Documentation · Souhaitée
- Analyse de données · Souhaitée
- Apprentissage automatique · Souhaitée
- MongoDB · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Python
- Machine Learning
- Data Analysis
- Model Development
- MongoDB
- Scikit-learn
- TensorFlow
- PyTorch
- Feature Engineering
- Hyperparameter Tuning
- Model Benchmarking
- MLOps
- Data Preprocessing
- Technical Documentation
- Cloud Deployment
- Inference Workflows
Domaines d’emploi
- Technology
- Software
- Engineering
- Data & Analytics
- Science & Research
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