About
Machine Learning Engineer Location: Philadelphia, PA Type:
Contract
Our client is seeking an experienced Machine Learning Engineer to serve in a senior-level data science role responsible for designing, developing, and implementing advanced time series forecasting models to predict future trends based on historical data.
We're seeking someone with experience building, training, and deploying real-world machine learning models from scratch, who thrives on turning data into working solutions and has extensive hands-on experience with end-to-end ML pipelines.
Key Accountabilities:
Lead the design and development of complex time series forecasting models using various techniques based on business needs. Thoroughly analyze large volumes of time series data to understand patterns, trends, seasonality, and potential anomalies. Fine-tune LLM models and work on time series models. Prototype and develop solutions for ML / LLM operations and Applied AI. Lead a team of data scientists and engineers focused on time series forecasting projects. Provide technical guidance, mentorship, and knowledge transfer to team members on time series analysis techniques and best practices.
Required Skills:
7 to 10 years+ of relevant work experience. Proven track record of building and shipping production ML models. Deep expertise in scikit-learn and core ML fundamentals (regression, classification, clustering, ensemble methods, feature engineering, model evaluation, etc.). Strong grasp of the entire ML lifecycle: data preprocessing, model selection, hyperparameter tuning, validation, and deployment. Exceptional ability to explain complex ML concepts (e.g., bias-variance tradeoff, overfitting, and gradient boosting) clearly and simply to non-technical stakeholders. Ability to open a notebook, build a model with scikit-learn, and then explain how and why it works would be a bonus.
171402-1
Languages
- English
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