Overview
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
Azure Machine Learning
K - Means
Regression
Scala
communication skills
Python
Google Cloud
scalability
Natural Language Processing
Computer Science
Job Details
Position Overview: We are seeking a highly skilled and experienced Machine Learning Engineer with expertise in handling both supervised and unsupervised datasets. The ideal candidate will possess a broad understanding of popular machine learning algorithms and ensemble techniques, along with a proven track record of optimizing machine learning models for real-world applications. In addition, the candidate should be proficient in visualizing and comparing algorithm results to derive meaningful insights.
Responsibilities:
- Develop and implement machine learning models for both supervised and unsupervised learning scenarios.
- Work on a variety of datasets, ensuring data quality and preprocessing to extract meaningful features.
- Utilize a wide range of machine learning algorithms and ensemble methods to create robust and accurate models.
- Optimize machine learning models for performance, scalability, and efficiency.
- Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions.
- Create visualizations to effectively communicate and compare algorithm results, aiding in decision-making processes.
- Evaluate the legitimacy of data sources and distinguish between valuable information and noise.
- Stay abreast of industry trends and advancements in machine learning to contribute innovative solutions.
Qualifications:
- Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
- Proven experience in developing machine learning models for real-world applications.
- Strong understanding of supervised and unsupervised learning techniques.
- In-depth knowledge of a variety of machine learning algorithms and ensemble methods, with experience using SVMs, Random Forests, Linear Regression, KNN, Nave-Bayes, K-Means, PCA, NNs, RNNs, & CNNs.
- Proficiency in optimizing machine learning models for performance and scalability, and familiarity with automated optimization algorithms.
- Demonstrated experience in visualizing and comparing algorithm results.
- Ability to assess the legitimacy of data sources and filter out noise.
- Strong programming skills in languages such as Python, R, PySpark, Scala, or similar.
- Excellent problem-solving and analytical skills.
- Effective communication skills to collaborate with cross-functional teams.
- Deep understanding of distributed data in cloud-based environments
- Familiarity with Google Cloud AI Platform for building, deploying, and managing machine learning models.
- Knowledge of Azure Machine Learning for building, training, and deploying machine learning models.
- Understanding of AWS SageMaker for building, training, and deploying machine learning models.
- Deep industry, local market, and broader market economic understanding as it affects model development & effectiveness.
- Ability to test the validity and/or effectively of predictive ML model results.
Preferred Skills:
- Experience with deep learning frameworks.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with big data technologies (e.g., Spark, Hadoop).
- Previous industry experience in [relevant industry/sector].