- 経験
- どれでも
- 給料
- USD 200,000 – USD 500,000 / year
- 求人情報
- 1
- 投稿済み
- 4時間前
- 作業モード
- 在宅勤務
- 再開する
- 応募必須
仕事内容
Role Summary
Our client is seeking a skilled AI/Machine Learning Engineer to design, develop, and deploy machine learning models that drive essential product functionalities. This full-time position is remote and offers a competitive annual salary ranging between $200,000 and $500,000. The engineer will collaborate with various teams to create scalable AI solutions aimed at improving user experience and operational workflows.
Key Responsibilities
- Create, train, and fine-tune machine learning models using Python along with TensorFlow and PyTorch libraries.
- Build and maintain efficient data pipelines to ensure quality data supports model training and assessments.
- Implement MLOps practices for smooth deployment, monitoring, and version management of models.
- Work closely with data scientists and software developers to embed AI features into live production systems.
- Perform performance benchmarking and conduct A/B testing to assess model effectiveness and business value.
Skills and Qualifications
- Strong coding expertise in Python, TensorFlow, and PyTorch tailored to model creation and training.
- Experience with MLOps platforms such as MLflow, Kubeflow, or SageMaker for comprehensive deployment and oversight.
- Deep understanding of data preprocessing techniques, feature engineering, and accuracy metrics for evaluation.
- Familiarity with major cloud service providers like AWS, GCP, or Azure to support scalable AI infrastructure.
- Knowledge of software engineering standards including source control with Git and implementing CI/CD pipelines.
Opportunity Details
This position offers a chance to contribute to a world-leading software company, tackling complex AI challenges using modern tools and rich datasets, fostering an innovative and cooperative work culture.
Equal Opportunity Employer Statement
The hiring process emphasizes merit and skills, welcoming candidates regardless of personal background or previous job history. Selection is made purely on technical competence and qualifications.