Machine Learning Engineer, Keeper Security
+ Above market annual bonuses
More information about location
Cybersecurity platform preventing password-related data breaches
Be an early applicant
Cybersecurity platform preventing password-related data breaches
201-500 employees
Be an early applicant
+ Above market annual bonuses
More information about location
201-500 employees
Company mission
To improve the safety and efficiency of online access by providing consumer and business users with vital password management, access management, and encrypted file storage software solutions.
Role
Who you are
- 3+ years of professional experience in ML research or development, with a focus on NLP and text classification
- Strong coding skills in Python, JavaScript, or a similar language relevant to ML
- Hands-on experience with fine-tuning large language models (BERT, RoBERTa, SBERT) for real-world tasks
- Experience with neural networks, autoencoders, LSTM for classification
- Strong understanding of the DOM API and web technologies (HTML, CSS, JavaScript)
- Proficiency with ML frameworks like TensorFlow, PyTorch, and Hugging Face Transformers
- Familiarity with MLOps, model deployment, and monitoring practices
- Experience with model validation and metrics (precision, recall, F1-score)
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Knowledge of secure coding, encryption, zero-trust, and zero-knowledge principles
- Excellent problem-solving and communication skills
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related discipline, or equivalent experience
What the job involves
- We are seeking a highly motivated and experienced Machine Learning Engineer to join our AI & Threat Analytics team
- As a Machine Learning Engineer, you will develop advanced autofill systems, focusing on multi-lingual text classification of HTML input fields using state-of-the-art techniques such as autoencoders and fine-tuned language models
- You’ll ensure that Keeper’s autofill features are fast, accurate, and intuitive, providing a seamless experience to millions of users globally
- You’ll collaborate closely with cross-functional teams to implement and optimize high-performance models that elevate Keeper’s product offerings
- Design and implement ML models for real-time DOM structure and form-field detection
- Fine-tune large language models for text classification, using projection layers and pooling
- Build and optimize feature extraction pipelines for HTML attributes, DOM structures, relationships, and text-based features
- Evaluate and fine-tune models using metrics like a confusion matrix, ROC/PR curves, and other techniques to optimize accuracy and performance
- Deploy models in our browser extension to support client-side inference
- Continuously improve model performance, accuracy, and runtime efficiency
- Troubleshoot and optimize production models for consistency and reliability
- Stay up-to-date with new ML frameworks (e.g., PyTorch, TensorFlow, Transformers) and incorporate improvements
- Scale ML pipelines and experimentation systems to support millions of users
- Collaborate with cross-functional teams to align ML efforts with product goals
- Write clean, maintainable code and provide comprehensive documentation
Our take
Keeper Security is a zero-trust and zero-knowledge cybersecurity platform looking to transform the way organizations and individuals secure their passwords. Allowing clients to have password security in minutes, Keeper seamlessly integrates with any tech stack to prevent possible breaches within businesses, in turn reducing help desk costs and ensuring compliance.
Trusted by over a million customers, Keeper is a proven industry leader in best-in-class password management, secrets management, privileged access, secure remote access, and encrypted messaging. The company has won a plethora of awards for its impact on the cybersecurity industry, including being named PC Magazine's Best Password Manager (2019-2022) and Editors Choice (2019-2022).
The company is partnered with some of the world's biggest organizations, including Google, Samsung, Amazon, Microsoft, LG, and Nokia, to enhance and protect individuals and businesses of all sizes across every major industry sector. Its most 2023 round of funding comes from influential Summit Partners, and this money will be used to accelerate growth and improve its cyber security tools. In short, then, Keeper Security seems well set to cement its position as a dominant market player.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
-1% employee growth in 12 months
Company
Funding (2 rounds)
Aug 2020
$60m
GROWTH EQUITY VC
Jan 2011
$0.3m
SEED
Total funding: $60.3m
Company values
- Integrity: Everything we do starts with being honest - about ourselves, the market opportunity and our collective responsibility to do right for each other and for our stakeholders
- Innovation: We don’t fear the abyss - we embrace it because that is where the greatest value creation exists
- Creativity: At Keeper, we embrace the power of imagination and creativity to drive industry-leading innovation
- Boldness: We push each other out of our comfort zones - to be courageous and entirely open-minded about taking measured risks that will transform our industry
- Collaboration: We operate flat, fast and efficient to deliver on unmet customer needs, at speed
- Accountability: The ability and willingness to take ownership is an essential component of our commitment to achieve greatness - as individual professionals and relied-upon team members
Company HQ
West Loop, Chicago, IL
Articles
Leadership
Darren Guccione
(CEO)Previously co-founded OnlyWire and Callpod. Also, previously the CFO & Director at Apollo Solutions.
Craig Lurey
(CTO)Previously founded Apollo Solutions (acquired by CNET Networks). Also worked as a CTO at JiWire.
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