Machine Learning Engineer

Nimbus Prime Partners; San Francisco (CA); On-site; USD 100,000 - 133,000; Full time

Benefits offered by this job

Health insurance

Retirement plan with employer matching

Tuition reimbursement

Access to online courses and workshops

Job summary

Nimbus Prime Partners seeks a Machine Learning Engineer in San Francisco, CA for full-time employment. You will design, train, and deploy ML models to solve complex financial challenges and forecast market trends.

Work with data scientists, software engineers, and product managers to integrate ML into trading platforms and risk tools. Strong Python skills and ML libraries are required; knowledge of AWS/GCP is a plus.

Qualifications

• Master's degree in Computer Science, Data Science, or a related field.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn.
• Experience with data processing and visualization tools like SQL, Pandas, and Matplotlib.

Responsibilities

• Develop, train, and deploy machine learning models to solve complex business problems.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Perform extensive data analysis and feature engineering to improve model performance.
• Stay up-to-date with advancements in ML and apply them to your work.
• Document work and share findings with the team.
• Participate in code reviews and provide constructive feedback.

Skills

Python

Strong communication

Team collaboration

Data analysis

Education

Master's degree in Computer Science / Data Science or related field

Tools

TensorFlow

PyTorch

scikit-learn

SQL

Pandas

Matplotlib

AWS/GCP

Job description

Nimbus Prime Partners seeks a Machine Learning Engineer in San Francisco, CA, for full-time employment. The role involves developing and implementing machine learning solutions to address complex financial challenges.

Daily tasks encompass designing and training predictive models to forecast market trends, optimizing algorithms to enhance computational efficiency and accuracy, and collaborating with cross-functional teams such as data scientists, software engineers, and product managers to integrate machine learning into financial products like trading platforms and risk assessment tools. This involves understanding the unique challenges and requirements of each team, ensuring seamless communication and alignment of goals.

The Machine Learning Engineer will join a team in San Francisco, CA, working in a collaborative environment focused on technological innovation in financial services.

The salary range for this position is between $100,000 and $133,226 per year, providing a competitive compensation package. In addition to the base salary, employees are offered comprehensive health insurance plans that cover medical, dental, and vision care. The company also provides a retirement plan with employer matching contributions, allowing employees to save for their future. Furthermore, professional development opportunities are available, including tuition reimbursement and access to online courses and workshops. These benefits aim to support the overall well-being and career growth of the employees.

Candidates must have a Master's degree in Computer Science, Machine Learning, or a related field, along with experience in Python, TensorFlow, and scikit-learn. Proficiency in SQL and knowledge of financial data are required.

What You Will Do:

• Develop, train, and deploy machine learning models to solve complex business problems.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Conduct extensive data analysis and feature engineering to improve model performance.
• Stay up-to-date with the latest advancements in machine learning and apply this knowledge to your work.
• Document your work and share your findings with the team.
• Participate in code reviews and provide constructive feedback to other team members.

What You Bring:

• A Master's degree in Computer Science, Data Science, or a related field, or equivalent experience.
• Strong programming skills in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
• Experience with data processing and visualization tools like SQL, Pandas, and Matplotlib.
• Knowledge of cloud platforms such as AWS or GCP and experience with cloud-based machine learning services.
• A passion for machine learning and a willingness to learn and adapt to new technologies.
• Excellent communication and teamwork skills.