Senior Machine Learning Engineer - Not an Active Opening, Building Talent Pipeline
Caylent · MEXICO
Posted about 3 months ago
or apply directly on Caylent's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 82 days Caylent's roles stay open a median of 81 days
- Reposted
- No
- Salary listed
- No 13% of Caylent's roles list one
- Ghost-job risk at Caylent
- high 88 stale, 12 reposted of 88 open
- Hiring momentum
- 143 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-24
Measured from postings appearing on and disappearing from Caylent's own greenhouse board since 2026-08-03. Full hiring picture for Caylent.
About this role
As a Senior Machine Learning Engineer at Caylent, you will work within a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for clients. Your responsibilities include developing and implementing ML models, participating in daily standups and bi-weekly agile ceremonies, and preparing training data for models, all while collaborating closely with your team and manager to align business goals with technical solutions.
- benefits
- 5/5
- freshness
- 1/5
- career value
- 4/5
- role clarity
- 4/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Caylent as an employer.
What you need
- Strong experience in building ML models for real world applications
- Strong experience in at least one of these: AWS ML Services/SageMaker, ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn, MLOps tools such as MLflow, Kubeflow, Airflow
- Advanced analytics using time series forecasting and/or inferential statistics
- Strong experience in one or more of these data processing solutions: Big data processing platforms like Spark, Hadoop, or streaming platforms, Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
- Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
- Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
What you get
- 100% remote work
- Medical Insurance for you and eligible dependents
- Generous holidays and flexible PTO
- Competitive phantom equity
- Paid for exams and certifications
- Peer bonus awards
Worth weighing
- This is not an active role currently; it is for building a talent pipeline for future opportunities.
- The position requires current legal authorization to work in the country where it is located; no visa sponsorship is available.
- The role may require up to 25% travel, depending on business needs.
Summarised from Caylent's posting. Read the full original.
Listed by Caylent on their greenhouse job board, last confirmed open on 2026-10-24. PitchMeAI is not the employer.
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