Machine Learning Engineer

4 days ago

Alexander City, United States augmentjobs Full time

Job Description:

Responsibilities:

  1. Algorithm Development: Design develop and implement machine learning algorithms and models to address business challenges and opportunities. Collaborate with crossfunctional teams to understand requirements define objectives and develop solutions that meet stakeholder needs.

  2. Data Collection and Preprocessing: Collect clean and preprocess large volumes of structured and unstructured data from diverse sources. Perform exploratory data analysis (EDA) to gain insights and identify patterns trends and anomalies in the data.

  3. Feature Engineering: Extract and engineer relevant features from raw data to improve model performance and predictive accuracy. Select appropriate features and transform data to optimize model training and evaluation.

  4. Model Training and Evaluation: Train validate and optimize machine learning models using appropriate techniques and methodologies. Evaluate model performance using metrics such as accuracy precision recall F1 score and ROC AUC and iteratively refine models as needed.

  5. Model Deployment: Deploy machine learning models into production environments integrating them into existing systems and workflows. Monitor model performance in realtime identify issues or drift and implement necessary updates or improvements.

  6. Scalability and Efficiency: Develop scalable and efficient machine learning solutions that can handle largescale data processing and analysis. Optimize algorithms and workflows for performance speed and resource utilization.

  7. Collaboration and Communication: Collaborate with data scientists software engineers and other stakeholders to drive projects forward. Communicate technical concepts and findings effectively to nontechnical audiences providing insights and recommendations for decisionmaking.

  8. Research and Innovation: Stay updated on the latest advancements in machine learning research methodologies and tools. Experiment with new techniques and technologies conducting research and prototyping to explore novel solutions to complex problems.

Qualifications:

  1. Education: Bachelors degree or higher in computer science engineering mathematics statistics or a related field. Advanced degrees (e.g. Masters or Ph.D.) are preferred but not required.

  2. Experience: Minimum of 35 years of experience in machine learning engineering data science or a related role. Proven track record of developing and deploying machine learning solutions in realworld applications.

  3. Programming Skills: Proficiency in programming languages commonly used in machine learning such as Python R or Julia. Experience with machine learning libraries and frameworks such as TensorFlow PyTorch scikitlearn or Keras.

  4. Data Skills: Strong data manipulation and analysis skills including experience working with large datasets and performing data preprocessing tasks. Familiarity with SQL NoSQL and big data technologies (e.g. Hadoop Spark) is a plus.

  5. Machine Learning Techniques: Solid understanding of machine learning algorithms techniques and methodologies including supervised and unsupervised learning deep learning reinforcement learning and ensemble methods.

  6. Software Engineering: Knowledge of software engineering principles and best practices including version control code review testing and debugging. Experience with software development lifecycle (SDLC) methodologies such as Agile or Scrum.

  7. ProblemSolving Skills: Strong analytical and problemsolving skills with the ability to understand complex problems formulate solutions and implement effective strategies to address them.

  8. Communication Skills: Excellent communication and interpersonal skills with the ability to collaborate effectively with crossfunctional teams and stakeholders. Ability to convey technical concepts and findings clearly and concisely.

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