Senior AI/ML Engineer

At SES AI, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $80,000 and $120,000. SES AI considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and skills.

What We Offer

• Company paid Health and Dental insurance (ability to add dependents)
• Global travel insurance for employees traveling while on business
• Company sponsored retirement plan with 100% vesting and up to 5% match.
• Life and AD&D Insurance
• Employee Assistance Program 
• Six Paid Holidays, and one floating holiday per a quarter equivalent to 4 per calendar year
• 10 accrued vacation days per calendar year that increases with tenure.
• Bonus + Equity, based on position and eligibility requirements

Note: SES AI benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 

About SES AI:
SES AI Corp. (NYSE: SES) is powering the future of global electric transportation on land and in the air with the world’s most advanced Li-Metal batteries. SES AI is the first battery company in the world to accelerate its pace of innovation by utilizing superintelligent AI across the spectrum of its business, from research and development; materials sourcing; cell design; engineering and manufacturing; to battery health and safety monitoring. Founded in 2012, SES AI is an Li-Metal battery developer and manufacturer headquartered in Boston and with operations in Singapore, Shanghai, and Seoul.

Learn more at SES.AI

This is a remote position.

Responsibilities:

• Design, develop, and implement machine learning models for battery state estimation and performance prediction.
• Fine-tune pre-trained models and establish the fine-tuning process and framework.
• Gather and preprocess large datasets from various sources to ensure data quality and consistency.
• Conduct system diagnostic and status estimation using supervised and unsupervised machine learning techniques.
• Develop predictive models to forecast battery performance
• Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.
• Maintain comprehensive documentation and reporting for model development and safety analysis processes.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, or a related field; PhD is a plus.
• Proficiency in programming languages such as Python, R, or MATLAB.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Strong statistical analysis and data visualization skills.
• Proven experience in developing and deploying machine learning models in performance prediction and state estimation applications.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work effectively in a fast-paced and dynamic environment.