Senior Machine Learning Engineer
New
J
JobgetherOnline Safety
Based in United StatesFull-TimeSenior
Salary154,000 - 212,750 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonKubernetesMachine LearningPyTorchTensorflowCI/CDTerraformNLPComputer Vision
Requirements
- 5+ years of experience in machine learning, artificial intelligence, or related technical fields.
- Master’s degree, Ph.D., or equivalent professional experience in a quantitative discipline such as computer science, mathematics, statistics, or engineering.
- Proven experience designing, developing, and deploying machine learning systems and production pipelines.
- Experience applying computer vision and/or natural language processing technologies in production environments.
- Strong programming skills in Python and experience with modern ML frameworks and tools.
- Experience with technologies such as PyTorch, TensorFlow/Keras, scikit-learn, Pandas, OpenCV, Hugging Face Transformers, or similar ML libraries.
- Familiarity with cloud infrastructure and engineering tools such as AWS, Kubernetes, Terraform, and CI/CD pipelines.
- Experience working with model optimization, deployment workflows, and scalable ML infrastructure.
- Ability to work effectively in ambiguous environments with evolving requirements.
- Strong collaboration skills with engineers, product teams, designers, and external stakeholders.
Responsibilities
- Own the complete machine learning lifecycle, including model design, development, testing, evaluation, deployment, and ongoing maintenance.
- Build and improve machine learning systems, classifiers, algorithms, and automated solutions to address complex online safety challenges.
- Identify data sourcing, labeling, and evaluation requirements while partnering with technical program teams to prioritize data initiatives.
- Collaborate with domain specialists to create effective data labeling strategies and improve model performance.
- Design and maintain production-ready ML pipelines, model serving infrastructure, and scalable engineering solutions.
- Partner with software engineers to integrate and maintain models, algorithms, and AI capabilities within products.
- Conduct data analysis, feature engineering, and experimentation to improve technical outcomes and product understanding.
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