Is Brainwave Science hiring on Feedback AI?

Brainwave Science has 1 active open role on Feedback AI today. Roles are listed for Boston, US and other hubs where posted. Browse open engineering listings on this company profile or sign up free to see AI match scores for each role.

How many open roles does Brainwave Science have?

Feedback AI tracks 1 active Brainwave Science job listing right now. Counts refresh from live postings — inactive listings are removed from the public board.

How does Feedback AI match candidates to Brainwave Science jobs?

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What is it like to interview at Brainwave Science?

This profile includes 3 Glassdoor-backed interview experiences when enrichment gates pass — process notes, difficulty, and sample questions where available.

Brainwave Science

51 to 200 Employees · Boston, US

3.1(19)

Brainwave Science headquartered in Boston, US has 1 active tech role on Feedback AI with AI match scores, optional skill assessments, and company insights when Glassdoor enrichment exists. Candidates browse open listings on this profile; signed-in users see ranked fit and skill gaps per role. Employers post jobs and review match-ranked applicants on the same platform.

Revenue Unknown / Non-ApplicableCEO approval 0%Business outlook 49%

Open roles tracked

Posted last 7 days

Posted last 30 days

Jobs at Brainwave Science ranked for your profile

Open roles at this company sorted by AI match score — skills, experience, and company fit when you are signed in. Guests browse the same roles on the public job board.

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Culture signals

Work-life balance 3.2
Compensation 3.0
Culture 3.3

What employees say

+ Great opportunities to learn and grow while working on cutting-edge technology. Talent is recognized and respected, and employees are given flexibility, ownership, and the freedom

− The high level of trust and flexibility can occasionally be misused by a small number of individuals, which may impact team productivity and place additional responsibility on othe

Employee voices

Recent Glassdoor reviews · 19 total

Research and Development· New DelhiFormer employee5.0/5

Excellent Learning Environment with High Trust and Flexibility

Pros: Great opportunities to learn and grow while working on cutting-edge technology. Talent is recognized and respected, and employees are given flexibility, ownership, and the freedom to contribute ideas. The work is challenging and provides valuable exposure across multiple domains.

Cons: The high level of trust and flexibility can occasionally be misused by a small number of individuals, which may impact team productivity and place additional responsibility on others. Stronger accountability and consistent enforcement of policies would help ensure everyone contributes fairly.

View on Glassdoor

R&D Associate· New DelhiCurrent employee1.0/5

Toxic environment with poor leadership and competition

Pros: Nothing in this category to be very honest

Cons: One of the worst companies I have ever worked for. There is a complete lack of communication and alignment between managers and departments. Instead of collaborating toward common business goals, teams seem more focused on competing with one another, creating a toxic and unproductive work environment. Leadership lacks clear direction, vision, and effective people management. Decisions often appear inconsistent, and employees are left uncertain about company priorities, long-term objectives, and overall strategy. For a company operating in the medical field, the absence of structured processes, clear standards, and professional governance is particularly concerning. What I found most disappointing was that I was encouraged to contribute and learn across different teams, yet this ultimately became a problem. Rather than supporting initiative, cross-functional learning and collaboration seemed to be discouraged. I was eventually terminated despite making genuine efforts to work with multiple teams and broaden my understanding of the business. Overall, the company suffers from poor leadership, internal conflicts, lack of organizational structure, and a culture that does not value employee growth or collaboration.

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Data Insights Analyst· New DelhiFormer employee1.0/5

Horrible Company!! Do NOT Join!

Pros: Zero. Waste of time and energy working here.

Cons: - No Learnings. Everytime you ask a question, they will say go and ask ChatGPT. - They won’t connect for weeks, won’t even look at the work shared. - They don’t know how to communicate. It’s surprising that top management has Horrible communication skills. Half of the time they are just repeating stuff one after another without any logic. - Illogical management - Deducted Hefty salary for taking 2 days of leaves - No induction with other teams. - Work culture doesn’t exist.

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AI / ML Developer· Bangalore RuralCurrent employee4.0/5

Intern experience

Pros: Remote work available in the group

Cons: Low pay as per industry standards

View on Glassdoor

Data Science Intern· NoidaFormer employee4.0/5

Great startup

Pros: innovative solutions, scope to brainstorm

Cons: base pay can be a bit more

View on Glassdoor

Company review data sourced from Glassdoor.

Compensation benchmarks

Glassdoor salary estimates for top hiring roles · 18 salary reports on Glassdoor

Role	Location	Median	Range (LPA)	Reports
Engineering	India	—	— – —	—

Salary benchmarks are estimates from Glassdoor and may differ from individual job listings.

Interview questions at Brainwave Science

3 questions indexed · 1 role tracks

Practice company sets

Software Engineer (3)

Underlying data structure in XGBoost and how XGBoost and Random Forrest Classification differ.
They asked mostly from the resume. They asked me about if there is a shortage of data as EEG data is difficult to curate, how would you handle it with the help of LLMs?
Are you aware with data analysis?

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Questions reported by interview candidates on Glassdoor; edited for clarity. Not guaranteed to match your exact interview.

Interview experiences

India-scoped Glassdoor interview reports · 3 total · avg difficulty 3.0/5 · 3 questions indexed

AI Research Engineer· New DelhiAveragedecline offer

Machine Learning Questions - Decision Trees, XGBoost. Fallback mechanisms and guardrails. Questions regarding Time-Series Data and constructing models and getting inferences, real time data analysis. EEG Data, Deep Learning Models, CNNs RNNs

Sample questions

Underlying data structure in XGBoost and how XGBoost and Random Forrest Classification differ.

AI Research Engineer· New DelhiAverageaccept offer

The interview is conducted in 4 rounds: 1. Introduction Round with HR 2. Technical Round 3. Discussions with CEO 4. Final HR round First round was a just a screening round and telephonic interview. Second was a call with Technical Manager with discussion about the LLMs, RAG, Deep Learning models, Time Series, Signal Processing, EEG Analysis etc. Then there was a call with CEO to discuss as a managerial round to check the company fit. Then, finally another round with HR to negotiate the salary and discuss other policies about the company.

Sample questions

They asked mostly from the resume. They asked me about if there is a shortage of data as EEG data is difficult to curate, how would you handle it with the help of LLMs?

AI Research Engineer· New DelhiAveragedecline offer

It was a smooth and efficient process. The HR team was very prompt in their response. It was excellent. I would highly recommend. Overall, it met my expectations. The depth in which we interacted was exceptional.

Sample questions

Are you aware with data analysis?

Top hiring roles: Engineering

Open engineering roles

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