Website Sony Electronics
Sony Electronics Inc. is looking for the risk-takers, the collaborators, the inspired and the inspirational. We want the people who are brave enough to work at the cutting edge and create solutions that will enrich and improve the lives of people across the globe. In addition to competitive pay and benefits, we offer an environment and culture that promotes Diversity, Equity and Inclusion. In addition, our team members enjoy innovative work-life balance opportunities including a hybrid home/office workplace, monthly “Free Fridays”, and early shutdowns on Fridays throughout the year (including half-days during the summer).
So, if you want to join a “Best Place to Work” company and make the world say wow, let’s talk.
Sony Electronics is seeking a Machine Learning Intern in San Diego, CA. We are looking for a talented, highly motivated individual to join the team responsible for developing next-generation visual AI solutions. The ideal candidate should have a passion for writing quality code and will be working on the implementation and validation of Computer Vision/Deep Learning algorithms for embedded platforms. In this role, you will develop self-supervised learning algorithms to collect and generate training data using large language model (LLM) for visual speech recognition, especially speech to text. This position is a great opportunity for a recent graduate looking to apply deep learning and computer vision skills to real-world business problems.
The internship is anticipated to last 6-12 months.
Responsibilities:
Review and learn groundbreaking research in advanced ML (e.g., semi-supervised and self-supervised learning), Visual Speech Recognition (VSR) and Natural Language Process (NLP) topics
Design and implement ML/AI solutions (e.g., self-supervised learning) for collecting and generating datasets for Large Language Model (LLM)
Curate and prepare data for VSR (e.g., speech-to-text) model development
Develop algorithms to improve the end-to-end performance of ML models
Perform hypothesis testing to determine feasibility of a ML or LLM applications
Minimum Qualifications:
Pursuing Master‡s degree or higher in a quantitative engineering field including computer science, mathematics, statistics, data science, or similar
Relevant applied course or work experience proving the ability to apply advanced analytics techniques to real-world problems
Understanding of standard data science practices
Strong written and verbal communication skills
Ability to be effective in a team environment
Curiosity and enthusiasm to learn new domains
Knowledge of Python or R or C/C++
Preferred Qualifications:
Experience with Big Data platforms, such as Spark, would be advantageous
Experience with self-supervised or reinforcement learnings are a plus
Experience with Speech-to-text(VSR), text-to-speech, or LLM are a plus
The anticipated hourly wage for this position is between $33.00 to $38.00. This range does not include any other compensation components or other benefits that an individual may be eligible for. The actual base wage offered depends on a variety of factors, which may include as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.
Sony Electronics is an Equal Opportunity Employer that values employees with a broad cross-cultural perspective. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, citizenship status, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.