11,949 Recommendation Systems jobs in India
AI Engineer | Recommendation Systems, Predictive Analytics
Posted 1 day ago
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted 1 day ago
Job Viewed
Job Description
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
Build intelligent recommendation engines using user behavior, property features, and contextual data.
Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
Optimize ML pipelines for performance, scalability, and low latency.
Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
Monitor model performance and iterate to improve accuracy, fairness, and relevance.
Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
3+ years of experience building and deploying machine learning models in production.
Strong background in recommendation systems, predictive analytics, or deep learning.
Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
Ability to work independently in a remote team environment.
Strong written and verbal communication skills.
Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
Experience in PropTech or real estate tech platforms.
Exposure to computer vision models (e.g., for floor plan or image analysis).
Contributions to open-source AI/ML projects.
Understanding of data privacy and ethical AI principles.
What We Offer
Competitive salary and performance bonuses
Flexible working hours and a fully remote team
Opportunity to innovate in a high-impact industry
Annual learning & development budget
A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
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AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture
AI Engineer | Recommendation Systems, Predictive Analytics
Posted today
Job Viewed
Job Description
Job Title: AI Engineer – PropTech | Recommendation Systems, Predictive Analytics
Location: 100% Remote (Work from Anywhere)
Job Type: Full-Time
Team: AI/ML Engineering
Experience Level: Mid to Senior Level
About the Role
We're seeking a results-oriented AI Engineer to help transform how real estate and property management work through cutting-edge AI solutions. In this remote role, you will lead efforts in building recommendation engines , predictive models , and automation frameworks that power intelligent decision-making for our platform.
Key Responsibilities
- Design and implement AI-driven solutions for property recommendations, pricing models, tenant screening, and predictive maintenance.
- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, PyTorch, or similar frameworks.
- Build intelligent recommendation engines using user behavior, property features, and contextual data.
- Collaborate with data engineers to ensure clean, high-quality datasets for model training and evaluation.
- Optimize ML pipelines for performance, scalability, and low latency.
- Work closely with product, design, and engineering teams to translate business needs into AI-powered features.
- Monitor model performance and iterate to improve accuracy, fairness, and relevance.
- Maintain best practices for reproducibility, version control, and documentation of models and experiments.
Requirements – Technical Skills
- 3+ years of experience building and deploying machine learning models in production.
- Strong background in recommendation systems, predictive analytics, or deep learning.
- Proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI, etc.).
- Solid understanding of statistics, feature engineering, model evaluation, and algorithm selection.
- Familiarity with data structures, RESTful APIs, and containerization (Docker/Kubernetes).
- Bonus: Experience with graph-based models or NLP for property-related applications.
Requirements – Collaboration & Communication
- Ability to work independently in a remote team environment.
- Strong written and verbal communication skills.
- Clear documentation and ability to explain technical concepts to non-technical stakeholders.
Nice to Have
- Experience in PropTech or real estate tech platforms.
- Exposure to computer vision models (e.g., for floor plan or image analysis).
- Contributions to open-source AI/ML projects.
- Understanding of data privacy and ethical AI principles.
What We Offer
- Competitive salary and performance bonuses
- Flexible working hours and a fully remote team
- Opportunity to innovate in a high-impact industry
- Annual learning & development budget
- A fast-paced, collaborative, and mission-driven culture