Overview :
Job Title : Senior Full-stack Engineer
Work Arrangement : Remote| Must be able to work EST hours
Job Type : Full-time
Salary : Competitive base salary in USD
Industry : PropTech / B2B SaaS / Real Estate Technology
Work Schedule : 40 hours per week
About Pearl Talent :
Hear why we exist, what we believe in, and who we’re building for: Watch here
Why Work with Us? :
About the company :
Our partner company helps the world’s most prominent companies navigate their most important brand, reputation, and product challenges. We specialize in high-impact research with hard-to-reach audiences -- recruiting the exact audiences our clients need, anywhere in the world. Our in-house teams ensure rigorous quality, rapid execution, and clear, strategic insights. Every engagement is custom-built, senior-led, and designed to deliver answers that drive key decisions.
Key Responsibilities
- Train and evaluate ML models using common machine learning frameworks in Python. Examples include TensorFlow, Keras, scikit-learn, or PyTorch.
- Develop and refine NLP pipelines (e.g., tokenization, entity recognition, similarity models).
- Perform fine-tuning and prompt engineering for LLMs (GPT, Claude, etc.).
- Create semantic search and recommendation models using vector embeddings and clustering techniques.
- Conduct experiments, hyperparameter tuning, and performance benchmarking.
- Collaborate with software engineers to integrate models into backend systems.
- Prepare clear documentation, model cards, and evaluation reports.
Requirements :
Required Skills :
- Strong proficiency in Python for machine learning and data processing.
- Experience with NLP libraries: spaCy, Hugging Face Transformers, gensim, nltk.
- Comfortable training deep learning models using Keras, TensorFlow, or PyTorch.
- Ability to design and execute ML experiments, evaluate models, and interpret results.
- Familiar with version control (Git), shell scripting, and Linux development environments.
- Basic back end software engineering skills, such as creating and managing endpoints, database services, and task queues.
- Experience with production environments (e.g., batch inference, model packaging)..
Nice to Have
- Experience with MLOps tools (e.g., MLflow, SageMaker, DVC).
- Contributions to Kaggle competitions, AI research, or open-source ML/NLP projects.
- Background in classical ML, unsupervised learning, or semantic modeling.
Working Conditions
- Fully remote, must be able to collaborate during EST hours.
- Focused environment for pure AI/ML development, research, and delivery.
Benefits :
Why Join Now
- Be a foundational member of a venture-scale company with real distribution advantages in real estate.
- Own key technical systems from day one, shaping how they evolve.
- Culture built on speed, iteration, and execution.
What You’ll Get :
- Professional Development: Annual learning budget for books, courses, and conferences
- Mentorship: Learn directly from startup veterans (ex-Looker, GitHub, Mulesoft)
- Impact: Help shape a growing brand with a voice that influences fintech innovation
- Inspiring Workspaces: Offices in Berlin, New York, and London, with travel opportunities
- Flat Hierarchy: Work directly with founders and have your ideas heard
- Flexible Work Setup: Equipment of your choice, strong home office support
Hiring Process :
- Application
- Screening
- Top-grading Interview
- Skills Assessment
- Client Interview
- Offer
- Onboarding
or continue with email
Job Title : Senior Full-stack Engineer
Work Arrangement : Remote| Must be able to work EST hours
Job Type : Full-time
Salary : Competitive base salary in USD
Industry : PropTech / B2B SaaS / Real Estate Technology
Work Schedule : 40 hours per week
About Pearl Talent :
Hear why we exist, what we believe in, and who we’re building for: Watch here
Why Work with Us? :
About the company :
Our partner company helps the world’s most prominent companies navigate their most important brand, reputation, and product challenges. We specialize in high-impact research with hard-to-reach audiences -- recruiting the exact audiences our clients need, anywhere in the world. Our in-house teams ensure rigorous quality, rapid execution, and clear, strategic insights. Every engagement is custom-built, senior-led, and designed to deliver answers that drive key decisions.
Key Responsibilities
- Train and evaluate ML models using common machine learning frameworks in Python. Examples include TensorFlow, Keras, scikit-learn, or PyTorch.
- Develop and refine NLP pipelines (e.g., tokenization, entity recognition, similarity models).
- Perform fine-tuning and prompt engineering for LLMs (GPT, Claude, etc.).
- Create semantic search and recommendation models using vector embeddings and clustering techniques.
- Conduct experiments, hyperparameter tuning, and performance benchmarking.
- Collaborate with software engineers to integrate models into backend systems.
- Prepare clear documentation, model cards, and evaluation reports.
Requirements :
Required Skills :
- Strong proficiency in Python for machine learning and data processing.
- Experience with NLP libraries: spaCy, Hugging Face Transformers, gensim, nltk.
- Comfortable training deep learning models using Keras, TensorFlow, or PyTorch.
- Ability to design and execute ML experiments, evaluate models, and interpret results.
- Familiar with version control (Git), shell scripting, and Linux development environments.
- Basic back end software engineering skills, such as creating and managing endpoints, database services, and task queues.
- Experience with production environments (e.g., batch inference, model packaging)..
Nice to Have
- Experience with MLOps tools (e.g., MLflow, SageMaker, DVC).
- Contributions to Kaggle competitions, AI research, or open-source ML/NLP projects.
- Background in classical ML, unsupervised learning, or semantic modeling.
Working Conditions
- Fully remote, must be able to collaborate during EST hours.
- Focused environment for pure AI/ML development, research, and delivery.
Benefits :
Why Join Now
- Be a foundational member of a venture-scale company with real distribution advantages in real estate.
- Own key technical systems from day one, shaping how they evolve.
- Culture built on speed, iteration, and execution.
What You’ll Get :
- Professional Development: Annual learning budget for books, courses, and conferences
- Mentorship: Learn directly from startup veterans (ex-Looker, GitHub, Mulesoft)
- Impact: Help shape a growing brand with a voice that influences fintech innovation
- Inspiring Workspaces: Offices in Berlin, New York, and London, with travel opportunities
- Flat Hierarchy: Work directly with founders and have your ideas heard
- Flexible Work Setup: Equipment of your choice, strong home office support
Hiring Process :
- Application
- Screening
- Top-grading Interview
- Skills Assessment
- Client Interview
- Offer
- Onboarding
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