Machine Learning Engineer

Who We Are

SQUIRE is the leading business management system designed for the needs of barbers, shop owners, and their communities.

We believe the pursuit of artistry and autonomy should not be restricted by the complexities of running a business.

With SQUIRE, we provide custom-branded tools, resources, and guidance to help barbers of all stages and experience levels attract and retain more customers, efficiently manage their shop operations, and increase their revenue.

Founded in ****, SQUIRE is trusted by more than 30,000 barbers across 5,000+ shops in more than a thousand cities worldwide.

From streamlined booking and opening new shops to real-time earning dashboards and building lasting customer relationships, SQUIRE supports shop owners in seamlessly bridging the gap between their personal craft and business goals.

SQUIRE enables barbers everywhere to unlock their full potential both as artists and as entrepreneurs.

For more information, please visit getsquire.com or download the SQUIRE app from the App or Play Store.

We're hiring a Machine Learning Engineer to embed into our product teams and own the entire ML lifecycle—from prototype to production.

This is not a role for model research or experimentation in a vacuum.

We're looking for an engineer who thrives on taking state-of-the-art ML (especially LLMs and AWS-based solutions) and transforming it into deployed, maintainable, and scalable real-world systems that power SQUIRE's products.

If you're passionate about building practical ML applications and turning ideas into shipping features, this role is for you.

Job Duties & Responsibilities

Own the full ML lifecycle for product features—from ideation to deployment, observability, and iteration

Use off-the-shelf models (e.g. in AWS SageMaker, Bedrock, Comprehend, HuggingFace) to solve core user and business problems

Build and maintain robust, scalable ML pipelines and infrastructure (batch and real-time)

Work cross-functionally with product managers, designers, and backend engineers to ship ML-powered features

Drive productionization: model inference, latency tuning, monitoring, logging, and failure recovery

Continuously evaluate and integrate emerging models (especially LLMs) to improve accuracy and capabilities

Bring an engineering mindset to ML work—automate processes, reduce tech debt, and champion good software practices in the ML stack

The duties and responsibilities outlined above are not a comprehensive list, and additional tasks may be assigned based on business needs.

Ideal Requirements & Qualifications

5+ years of experience in machine learning engineering, ideally within a product-oriented tech team

1+ years of experience building GenAI/LLM-based features and products: chat bots, agents, features based on Gen AI

You know the challenges of building AI features.

Model choise, orchestration, hallucinations, RAG, etc.

Ability to stitch together different services to make a production-ready Gen AI solution.

Strong software engineering background with experience writing clean, scalable, and maintainable code in Python

Hands-on experience using cloud-based ML services (especially AWS) and pre-trained models in production

Experience with modern deployment stacks and MLOps: CI/CD, model versioning, monitoring, etc

A pragmatic mindset—you value impact, simplicity, and reliability over academic perfection

NICE TO HAVE

Experience integrating LLMs into products via APIs or fine-tuning

Familiarity with React Native applications or full-stack development environments

Prior work in consumer or SMB-facing products.

A Gen-AI-based side project that was used by real users that you can present.

Experience or willingness to own AI features end-to-end - from the ML/LLM part to making sure it is connected to our db and runs well on our backend.

WHY JOIN SQUIRE?

Work on impactful, customer-facing features powered by machine learning

Help shape our AI-first engineering culture

Enjoy autonomy and ownership over your domain with the support of an exceptional engineering team

Competitive salary, equity, and benefits in a high-growth, mission-driven company

Interview Accommodations

SQUIRE is committed to working with and providing reasonable assistance to individuals with physical and mental disabilities.

If you are an individual with a disability requiring an accommodation to apply for an open position, please email your request to ****** and someone on our team will respond to your request.

Equal Employment Opportunity

SQUIRE provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Pay Transparency Nondiscrimination Provision

SQUIRE will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.

However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is

• in response to a formal complaint or charge,
• in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or
• consistent with the contractor's legal duty to furnish information.
  
  

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