At PriceAdvantage, a division of Skyline Products, we have revolutionized the way fuel marketers price fuel by giving them easier access to real-time data, eliminating manual processes, and decreasing the time it takes to execute fuel price changes accurately. With these core competencies, PriceAdvantage has helped fuel retailers across the country increase their profitability significantly.
The ideal candidate will have a strong background in machine learning algorithms and data analysis, with experience in developing and deploying machine learning models. This role involves collaborating with cross-functional teams to enhance our data-driven decision-making processes and improve product offerings.
We are looking for a Remote Machine Learning Engineer to join our team, where you will play a key role in developing cutting-edge AI and machine learning models that drive innovative solutions across various applications. You will work with cross-functional teams to design, build, and deploy intelligent systems that improve performance, efficiency, and user experiences. Your expertise in AI algorithms, machine learning frameworks, data analysis, and software development will contribute to solving complex business problems and advancing our technological capabilities.
Key Responsibilities:
Design, develop, and implement AI-driven solutions using machine learning techniques, deep learning, natural language processing (NLP), and computer vision
Build, train, and optimize machine learning models to analyze large datasets and derive actionable insights
Develop and integrate machine learning algorithms into production systems, ensuring scalability and performance
Collaborate with data scientists, software engineers, and other stakeholders to define system requirements, data pipelines, and performance metrics
Utilize big data tools and frameworks to process, analyze, and extract insights from large datasets in various domains
Continuously improve model performance through experimentation, hyperparameter tuning, and model evaluation
Stay updated with the latest AI and machine learning research trends to apply cutting-edge technologies and techniques. Implement best practices in coding, version control, and continuous integration for projects.
Required Skills & Qualifications: Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Keras, Scikit-learn).
Troubleshoot and resolve issues related to machine learning models and AI applications
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
Strong proficiency in programming languages such as Python, Java, or C++
Solid understanding of AI techniques, including supervised and unsupervised learning, reinforcement learning, NLP, and deep learning
Proficiency in data manipulation and analysis using tools such as Pandas, NumPy, and SQL
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying models
Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)
Strong problem-solving and analytical skills, with the ability to work on complex data-driven projects
Excellent communication skills and the ability to work collaboratively in a multidisciplinary team
Preferred Qualifications:
Familiarity with data engineering concepts and tools, including ETL processes and data warehousing
Knowledge of distributed computing and high-performance computing (HPC) for scaling machine learning models
Familiarity with Agile methodologies and version control systems (e.g., Git)
Compensation:
The compensation for this position ranges from $100,000 - $120,000 depending on experience.
Why Join Us?
As part of our dynamic team, you will have the opportunity to work on some of the most exciting and impactful AI and machine learning projects in the industry. We foster a collaborative environment where innovation is encouraged, and we provide the tools and resources you need to grow your career in AI and machine learning.
Skyline Products is an Equal Opportunity Employer; all decisions are made without regard to race, color, religion, creed, gender, national origin, age, disability, marital or veteran status, ual orientation, gender identity, or any other legally protected status.
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