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Lilo AI

Data Engineer / Machine Learning Engineer in Lilo AI

FULL_TIME

Santiago
This job is performed partly from home and partly at the office in: Santiago
(Hybrid)
| Senior | Full time | Machine Learning & AI

Gross salary $3000 - 4000 USD/month

1 applications
Replies between 1 and 9 days
Last checked today
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Requires applying in English
Lilo AI is an innovative startup dedicated to transforming procurement for Commercial Real Estate (CRE) businesses by creating the most hassle-free procurement platform globally. Our platform leverages artificial intelligence to automate and optimize various procurement workflows, including invoicing, vendor management, and price comparisons. Serving diverse sectors such as hotels, gyms, schools, and senior living homes, our solutions save clients valuable time and money while improving operational efficiency. Our major clients include prestigious brands such as Fairfield, Hampton Inn, and Hilton. By joining Lilo AI, you will contribute to revolutionizing procurement processes at scale through cutting-edge AI technologies.

This job offer is on Get on Board.

About the Role

As a Data Engineer / Machine Learning Engineer at Lilo AI, you will play a pivotal role in advancing and deploying machine learning solutions that enhance our procurement platform. Your primary responsibilities will include:
  • Designing, developing, and implementing machine learning models to optimize procurement workflows, such as price prediction algorithms, anomaly detection systems, and recommendation engines.
  • Building and maintaining robust data pipelines to efficiently preprocess and cleanse both structured and unstructured datasets.
  • Collaborating closely with engineers, product managers, and business stakeholders to integrate AI-driven insights seamlessly into our platform environment.
  • Optimizing model performance and reliability, including contributing to monitoring strategies and retraining pipelines to sustain production quality.
  • Keeping abreast of the latest developments in AI, machine learning, and data science to continually enhance our technology stack.
  • Supporting the deployment of machine learning models into production environments and improving MLOps workflows to increase operational efficiency.
This role requires a proactive mindset, a passion for AI applications in real-world business contexts, and the ability to thrive in a dynamic, fast-paced, and collaborative global team.

What You Will Need

To succeed in this role, candidates should demonstrate strong technical proficiency and relevant experience as detailed below:
  • A minimum of 2 years of professional experience in machine learning, data science, or closely related fields.
  • Proficiency in Python programming and familiarity with prominent ML frameworks and libraries such as Scikit-Learn, TensorFlow, or PyTorch.
  • Hands-on experience with both SQL and NoSQL databases, including but not limited to MongoDB and PostgreSQL.
  • Solid understanding of data preprocessing techniques, feature engineering, and model evaluation methodologies essential for robust ML model development.
  • Basic knowledge or experience with containerization (Docker), cloud computing platforms (AWS, Google Cloud Platform, or Azure), and MLOps tools is highly desirable.
  • Analytical mindset with strong problem-solving skills, able to handle and extract insights from large datasets effectively.
  • A continuous learner attitude, eager to develop technical and professional skills while contributing to team goals.
We value curiosity, collaboration, and adaptability, wanting individuals who are ready to grow alongside our rapidly expanding company.

Desirable Skills and Experience

While not mandatory, the following skills and experiences will give candidates an edge:
  • Experience working with time-series data, demand forecasting, or procurement-related AI models.
  • Familiarity with advanced ML techniques such as deep learning, reinforcement learning, or natural language processing.
  • Hands-on exposure to MLOps pipelines, automated model deployment, and monitoring platforms.
  • Knowledge of data engineering tools and frameworks like Apache Airflow, Spark, or Kafka.
  • Prior experience in the hospitality or Commercial Real Estate sectors.
  • Strong communication skills to effectively articulate technical concepts to non-technical stakeholders.

Why Lilo AI?

Joining Lilo AI offers a unique opportunity to make a significant impact at a fast-growing US-based startup while enjoying the flexibility of remote work from Latin America. We provide:
  • A high-impact role within a pioneering team revolutionizing procurement with AI.
  • Possibility to grow professionally with opportunities to increase responsibilities over time.
  • Stock options available for the right candidate, sharing in our long-term success.
  • A collaborative, global, and multi-cultural work environment fostering innovation and continuous learning.

GETONBRD Job ID: 54612

Pet-friendly Pets are welcome at the premises.
Flexible hours Flexible schedule and freedom for attending family needs or personal errands.
Partially remote You can work from your home some days a week.
Health coverage Lilo AI pays or copays health insurance for employees.
Company retreats Team-building activities outside the premises.
Dental insurance Lilo AI pays or copays dental insurance for employees.
Computer provided Lilo AI provides a computer for your work.
Informal dress code No dress code is enforced.
Vacation over legal Lilo AI gives you paid vacations over the legal minimum.

Remote work policy

Hybrid

This job is performed partly from home and partly at the office in Santiago (Chile).

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About Lilo AI

We are creating the most hassle-free procurement platform on the planet. We want to empower our customers to streamline their operations, boost their profits, and free up valuable time for what really matters. — Lilo AI's full profile

Data Engineer / Machine Learning Engineer
Lilo AI • Santiago
This job is performed partly from home and partly at the office in: Santiago
(Hybrid)
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Requires applying in English
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