Checksum

Benefits:

• Competitive salary and benefits package

• Lunch 3 days a week in office

Education Requirements:

• Bachelor’s Degree in Computer Science, Statistics, Applied Mathematics, or other related fields.

• PhD (preferred)

Experience Requirements:

• 8+ years of software engineering experience

• 4+ years of engineering management experience

Other Requirements:

• Strong coding skills in JavaScript and TypeScript.

• Proven ability to collaborate with stakeholders, including customers, and translate feedback into actionable solutions.

• Excellent project management skills, with the ability to define and track success criteria.

• Strong problem-solving abilities and attention to detail.

• Experience with end-to-end test automation frameworks and building test suites.

• Hands-on experience in QA processes, with a focus on automation

Responsibilities:

• Lead customer implementation of end-to-end testing pipeline, ensuring high-quality software delivery.

• Build and maintain end-to-end test automation frameworks and suites.

• Work directly with customers, fostering empathy and ensuring their needs are met through efficient solutions.

• Drive customer success, implementation and revenue expansion.

• Write, review, and debug code in JavaScript and TypeScript to support both development and QA automation efforts. Collaborate closely with the Co-Founder and cross-functional teams to set and achieve clear success criteria.Support and mentor QA team members, helping to develop their technical and professional skills.Drive projects from inception to completion, ensuring timelines and deliverables are met

Benefits:

• Competitive salary and generous equity

Education Requirements:

• Bachelor’s Degree in Computer Science, Statistics, Applied Mathematics, or other related fields.

• PhD (preferred)

Experience Requirements:

• 5+ years of experience in developing end to end ML-related software solutions, involving substantial software development efforts, 3+ years of hands-on experience with Python.

• 2+ years of professional experience with NLP, 1+ years of professional experience with Large Language Models (LLM)/GenAI technology like OpenAI API, ChatGPT, GPT-4, Bard, Langchain, HuggingFace Transformers, PyTorch and similar, 1+ years of experience with prompt engineering and agent development, 1+ years of experience with vector databases, RAG concepts.

• 1+ years of experience with fine-tuning open source LLMs, familiarity with PEFT, model quantization & optimization techniques such as GPTQ, (Q)LoRA.

• 2+ years of experience with AWS, GCP or Microsoft Azure, 2+ years of experience with MLOps, CI/CD pipeline development, containerization, model deployment in test and production environments.

• Solid understanding of backend development principles, including software architecture, API design, databases, and server-side frameworks. Proficiency in data preprocessing techniques, exploratory data analysis and feature engineering

Responsibilities:

• Lead the ML efforts towards tackling this one of a kind challenge

Benefits:

• Competitive salary and generous equity

Education Requirements:

• Bachelor’s degree from a well-known institution in Computer Science or a parallel degree including substantial computer science fundamentals studies (e.g. Electrical Engineering, Industrial Engineering, Information Technology)

Experience Requirements:

• 3+ years of software engineering with significant backend services development and web application design and development (either as a full-stack engineer or any other eng. position with experience developing web apps)

Other Requirements:

• Substantial experience working with Node.js and Javascript/Typescript

• High familiarity with web development concepts and technology - DOM, HTML, Javascript, CSS, etc

• Solid programming foundations - data-structures, OOP, design patterns, complexity analysis, building and consuming APIs, databases, etc

• Experience with algorithm design and implementation, using heuristics, working with sequential data, traversing trees and graphs, evaluating and improving results