Machine Learning Engineer

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Machine Learning Engineer

Contract

100% Remote

Position Overview:

As a Machine Learning Developer/Engineer, you will play a crucial role in designing, developing, and deploying machine learning models and systems that drive data-driven decision-making and enhance the overall functionality of our products/services. You will collaborate closely with cross-functional teams including data scientists, software engineers, and domain experts to translate business requirements into actionable machine learning solutions.

Key Responsibilities:

• Develop and implement machine learning algorithms for analyzing multi-variate time series data, extracting meaningful patterns, and making accurate predictions.
• Design and implement data preprocessing pipelines to clean, transform, and aggregate time series data for model training and evaluation.
• Collaborate closely with domain experts to understand the context and nuances of the time series data, ensuring that the developed models address real-world challenges.
• Research and experiment with state-of-the-art time series analysis techniques, selecting the most appropriate algorithms for different data scenarios.
• Explore feature engineering techniques and dimensionality reduction methods tailored to time series data characteristics.
• Fine-tune and optimize models to achieve high predictive accuracy, considering factors like model complexity, interpretability, and computational efficiency.
• Work closely with software engineers to integrate developed models into production systems, ensuring seamless and efficient deployment.
• Monitor model performance in real-world environments, identifying and addressing potential issues to maintain reliable predictions over time.
• Stay current with advancements in time series analysis, machine learning, and related fields, and apply that knowledge to enhance the team's capabilities.
• Collaborate with cross-functional teams to communicate technical concepts and findings to both technical and non-technical stakeholders.

Qualifications and Skills:

·        Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. PhD is a plus.

·        Strong understanding of time series analysis concepts, algorithms, and techniques.

·        Proficiency in programming languages such as Python, and experience with libraries like TensorFlow, PyTorch, scikit-learn, and specialized time series libraries (e.g., statsmodels, Prophet).

·        Experience with handling and preprocessing multi-variate time series data, including feature extraction and data normalization.

·        Experience with open source ML regression models like XGBoost, CatBoost, LightGBM

·        Familiarity with machine learning techniques such as LSTM, GRU, attention mechanisms, and ensemble methods applied to time series data.

·        Strong analytical and problem-solving skills, with an ability to think critically about model outputs and tune hyperparameters effectively.

·        Familiarity with cloud platforms and services (e.g.. Azure) for deploying machine learning solutions is advantageous.

·        Knowledge of version control systems (e.g., Azure DevOps), data visualization tools, and agile development methodologies.

·        Excellent communication skills to collaborate with interdisciplinary teams and present findings to stakeholders.

·        Previous experience with real-world deployment of time series models in production environments is a plus.

Brooksource provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

Brooksource provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

JO-2308-138927

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