134 applicants

Company

Original Job Post

Optimum Energy · 5 days ago

Software Development Engineer for Machine Learning

Seattle, WA

Full-time

Onsite

Senior Level

$125K/yr - $170K/yr

5+ years exp

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EnergyEnergy Efficiency

Comp. & Benefits

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Responsibilities

Design, implement, and maintain SaaS based applications as well as tools to streamline solution delivery by internal teams and partners.

Evaluate potential improvements for existing prototypes and refine them to enhance performance and scalability.

Architect comprehensive ML solutions that align with company objectives, ensuring they are robust and scalable.

Identify and apply the most suitable machine learning techniques and tools to solve complex problems effectively.

Choose the most appropriate datasets and methods for data representation to maximize the accuracy and efficiency of machine learning models.

Execute rigorous tests and experiments to validate the performance of machine learning models under various conditions.

Perform detailed statistical analysis and refine machine learning models based on the insights gathered from test results.

Regularly train, retrain, and maintain machine learning systems to adapt to new data and evolving requirements.

Contribute to the enhancement of existing machine learning libraries and frameworks, improving their functionality and efficiency.

Continuously update knowledge of new technologies, techniques, and industry trends in machine learning and AI to keep solutions at the forefront of innovation.

Develop software using object-oriented design and state-of-the-art design patterns for service-oriented architectures.

Participate as an active member of a Scrum team including feature definition, Sprint planning activities, daily stand-ups, task and test management, and retrospectives.

Document software functionality and provide 3rd tier support for developed applications.

Participate in design and code reviews.

Collaborate with subject matter experts, Product and Development managers to define technical strategy, plan projects, develop requirements, write specifications.

Quickly acquire knowledge of HVAC control systems, data collection, and energy consumption, baseline and savings calculation methods.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningData StructuresData ModelingSoftware ArchitectureMathematicsProbabilityStatisticsAlgorithm DevelopmentProgramming Languages PythonProgramming Languages JavaProgramming Languages RMachine Learning Frameworks KerasMachine Learning Frameworks PyTorchMachine Learning Libraries (scikit-learn)Graph Data StructuresRelational Databases (PostgreSQL)NoSQL Databases (Redis)Time-Series Data AnalysisCloud PlatformsDesign PatternsProduct OwnershipProblem-SolvingCommunicationAnalytical SkillsInnovative ThinkingCollaborationPython

Required

Minimum 5 years of experience in developing enterprise SaaS applications.

BA/BS in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience.

Proven track record as a Machine Learning Engineer or in a similar capacity, showcasing successful project completions and innovative solutions.

Solid understanding of data structures, data modeling, and software architecture, essential for developing effective machine learning systems.

In-depth knowledge of mathematics, probability, statistics, and algorithm development necessary for high-level data analysis and model creation.

Proficient in writing clean, efficient code in multiple programming languages including Python, Java, and R, tailored for scalable machine learning solutions.

Well-versed in various machine learning frameworks (such as Keras or PyTorch) and libraries (like scikit-learn), enabling the development and deployment of advanced models.

Exceptional communication skills, capable of clearly articulating complex technical details and collaborating effectively with cross-functional teams.

Outstanding analytical skills to tackle complex problems through logical reasoning and innovative thinking.

Proficiency in working with graph data structures and developing complex data structures and algorithms.

Expertise in relational databases (e.g., PostgreSQL) and familiarity with NoSQL databases (e.g., Redis).

The candidate must possess specialized experience in analyzing and modeling time-series data, demonstrating proficiency in applying machine learning techniques to sequential data sets such as financial trends, sensor data, or continuous monitoring metrics.

Strong experience with cloud platforms for scaling machine learning workloads. The candidate should have a track record of efficiently deploying, managing, and optimizing large-scale ML systems in the cloud, ensuring robust performance and high availability.

Understanding of design patterns, best practices for scalable and highly available systems, and a strong sense of product ownership.