Bear Robotics Salary in United States during 2024

Salary details

The average Bear Robotics salary lies between USD 88,000 and USD 205,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 10, 2024

Top 20 Job Tags for Bear Robotics roles

The three most common job tag items assiciated with Bear Robotics job listings are Robotics, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Robotics | 12 jobs Python | 9 jobs Engineering | 7 jobs Linux | 6 jobs Computer Science | 5 jobs Machine Learning | 4 jobs Tableau | 4 jobs Security | 4 jobs Git | 4 jobs Looker | 3 jobs Testing | 3 jobs GCP | 3 jobs Pipelines | 3 jobs SLAM | 2 jobs OpenCV | 2 jobs SQL | 2 jobs Power BI | 2 jobs Architecture | 2 jobs Data visualization | 2 jobs Terraform | 2 jobs

Top 20 Job Perks/Benefits for Bear Robotics roles

The three most common job benefits and perks assiciated with Bear Robotics job listings are Career development, Flex hours and Team events. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 4 jobs Flex hours | 2 jobs Team events | 2 jobs 401(k) matching | 1 jobs Lunch / meals | 1 jobs Equity / stock options | 1 jobs Parental leave | 1 jobs Flex vacation | 1 jobs Wellness | 1 jobs Health care | 1 jobs Startup environment | 1 jobs Medical leave | 1 jobs Insurance | 1 jobs Salary bonus | 1 jobs Flexible spending account | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the AI/ML/Data Science field, the salary composition can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration. The base salary is the fixed amount that you receive regularly, and it often constitutes the largest portion of your total compensation. Bonuses can be performance-based or company-wide and may vary annually. Additional remuneration might include stock options, profit-sharing, or other incentives, which are more common in larger tech companies or startups. In regions with a high cost of living, such as Silicon Valley, the base salary might be higher to compensate for living expenses, while in smaller markets, bonuses and stock options might play a more significant role in attracting talent.

Steps to Increase Salary

To increase your salary from a position in AI/ML/Data Science, consider the following strategies:

• Skill Enhancement: Continuously update your skills with the latest technologies and methodologies in AI and machine learning. Specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's or Ph.D., can open up higher-paying opportunities and leadership roles.

• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and engaging with thought leaders in the field.

• Performance and Negotiation: Consistently demonstrate high performance and be prepared to negotiate your salary during performance reviews or when taking on additional responsibilities.

• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if the new company values your specific skill set more highly.

Educational Requirements

Most positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or even a Ph.D., especially for more advanced roles. A strong foundation in mathematics, particularly in areas like linear algebra, calculus, and probability, is essential. Additionally, coursework in computer science, data structures, algorithms, and machine learning is highly beneficial.

Helpful Certificates

While not always mandatory, certain certifications can enhance your resume and demonstrate your commitment to the field. Some popular certifications include:

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills and knowledge, making you a more attractive candidate to potential employers.

Required Experience

The typical experience required for an AI/ML/Data Science role varies, but most positions require at least 2-5 years of relevant experience. This experience can be gained through internships, research projects, or previous roles in data analysis, software development, or related fields. Experience with programming languages such as Python or R, as well as familiarity with machine learning frameworks like TensorFlow or PyTorch, is often expected.

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