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Day 20
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Reads like a ML Engineer role: putting models into production.
Lima, Callao Region, Peru
Live, first seen by us 20 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Build and evaluate ML approaches for company and entity matching
Develop embedding and LLM-based matching approaches
Develop scoring and ranking to separate true matches from duplicates and lookalikes
Define benchmark datasets, metrics, baselines, and error-analysis processes
Compare LLM-assisted approaches against lower-cost alternatives
Build and evaluate ML approaches for company/entity matching.
Develop embedding and LLM-based matching approaches.
Develop scoring and ranking methodologies to identify true matches and distinguish them from duplicates, lookalikes, and unrelated entities.
Define benchmark datasets, metrics, baselines, and error-analysis processes.
Compare LLM-assisted approaches against lower-cost alternatives.
5+ years of professional Data Science / Machine Learning experience.
Hands-on experience with embeddings and semantic similarity.
Excellent Python and SQL skills.
Practical experience applying LLMs to real-world problems.
Hands-on experience with TensorFlow, PyTorch, PyCaret, or equivalent ML frameworks.
At Applaudo, talented people design, build, and scale meaningful, AI-powered solutions that create real business impact.
In the employer’s words · Read in context
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Day 20
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Strong applied Machine Learning fundamentals. - Excellent Python and SQL skills. - Hands-on experience with embeddings and semantic similarity.
- LLM/embedding solutions designed for cost and scale constraints. - Spark, Snowflake, Databricks, or BigQuery. - Experience with company, domain, website, or firmographic data.
- Working knowledge of neural networks and transformer architectures. - Hands-on experience with TensorFlow, PyTorch, PyCaret, or equivalent ML frameworks. - Experience retraining or maintaining classification models in production.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
About You
You are an experienced Data Scientist with strong applied Machine Learning expertise and a track record of building and evaluating models using real-world, messy, large-scale data. You are comfortable working with embeddings, semantic similarity, LLMs, NLP, classification, and both supervised and unsupervised learning. You approach ambiguous problems through structured experimentation, clearly defined hypotheses, baselines, metrics, and error analysis.
You are highly autonomous, intellectually honest about experimental results, and able to clearly communicate technical recommendations and trade-offs to engineering and business stakeholders.
You Bring to Applaudo the Following Competencies
Nice-to-Have
You Will Be Accountable for the Following Responsibilities
What Sets You Apart
About Us
We Are Engineered Different.
At Applaudo, talented people design, build, and scale meaningful, AI-powered solutions that create real business impact. As an AI-native organization, we collaborate across design, development, cloud, data, and artificial intelligence to turn ideas into scalable products that transform how companies operate, make decisions, and grow.
We are building a high-performance culture grounded in five values: Empowering Excellence, Collaborative Teamwork, Unsolicited Respect, Consistent Transparency, and Efficient Communication. These define how we work, how we support one another, and how we hold ourselves accountable.
Applaudo is a place for people who want to learn fast, take ownership, and work alongside strong teams they are proud to belong to. Joining us means being part of an organization that is evolving intentionally, investing in modern ways of working, and leading AI-native transformation at scale.
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Lima, Callao Region, Peru
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