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AI-Powered Job Summary
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Data Scientist / Machine Learning Engineer
to develop and enhance our data and analytics infrastructure. The position is
FULLY REMOTE
, based in Latin America. Professional English proficiency (B2/C1)
This position will provide you with the opportunity to collaborate with a dynamic team and talented data scientists in the field of big data analytics and applied
AI
- If you have a passion for designing and implementing advanced machine learning and deep learning models, particularly in the
space, this role is perfect for you. We are seeking a skilled professional with expertise in
Python
for production-level projects, proficiency in machine learning and deep learning techniques such as
CNNs
and
Transformers
, and hands-on experience working with
PyTorch
We're looking for a versatile
Machine Learning Engineer / Data Scientist
to join our big-data analytics team. In this hybrid role you'll not only design and prototype novel
ML/DL models
, but also productionize them end-to-end, integrating your solutions into our data pipelines and services. You'll work closely with data engineers, software developers and product owners to ensure high-quality, scalable, maintainable systems.
Key Responsibilities
Model Development & Productionization
Design, train, and validate supervised and unsupervised models (e.g., anomaly detection, classification, forecasting).
Architect and implement deep learning solutions (CNNs, Transformers) with
PyTorch
Develop and fine-tune Large Language Models (LLMs) and build LLM-driven applications.
Implement Retrieval-Augmented Generation (RAG) pipelines and integrate with vector databases.
Build robust pipelines to deploy models at scale (
Docker
,
Kubernetes
,
CI/CD
).
Data Engineering & MLOps
Ingest, clean and transform large datasets using libraries like
pandas
,
NumPy
, and
Spark
Automate training and serving workflows with
Airflow
or similar orchestration tools.
Monitor model performance in production; iterate on drift detection and retraining strategies.
Implement
LLMOps
practices for automated testing, evaluation, and monitoring of LLMs.
Software Development Best Practices
Write production-grade
Python
code following
SOLID
principles, unit tests and code reviews.
Collaborate in
Agile (Scrum)
ceremonies; track work in
JIRA
Document architecture and workflows using
PlantUML
or comparable tools.
Cross-Functional Collaboration
Communicate analysis, design and results clearly in English.
Partner with DevOps, data engineering and product teams to align on requirements and SLAs.
About Azumo
Based in San Francisco, California,
Azumo
is an innovative software development firm specializing in
AI software development services
- We help companies of all sizes build intelligent applications by combining expertise in data, cloud, and
- Our talented
are trusted to deliver
Top AI Development services
in
Generative AI
, intelligent automation, and custom machine learning solutions.
At
Azumo
, we believe in professional and personal growth. As a recognized
AI Development company
, we support our engineers in mastering the latest technologies and delivering
Top AI Development services
worldwide. Our culture emphasizes collaboration, continuous learning, and solving complex problems with modern
AI
solutions. We believe in giving back to our community and will volunteer our time to philanthropy, open-source initiatives and sharing our knowledge.
If you are qualified for the opportunity and looking for a challenge please apply online at Azumo/join-our-team or connect with us at ******
Requirements
Minimum Qualifications
Bachelor's or Master's in Computer Science, Data Science or related field.
5+ years
of professional experience with
Python
in production environments.
Solid background in machine learning & deep learning (
CNNs
,
Transformers
,
LLMs
).
Hands-on experience with
PyTorch
or similar frameworks (training, custom modules, optimization).
Proven track record deploying
ML solutions
Expert in
pandas
,
NumPy
and
scikit-learn
Familiarity with
Agile/Scrum
practices and tooling (
JIRA
,
Confluence
).
Strong foundation in
statistics
and experimental design.
Excellent written and spoken English.
Preferred Qualifications
Experience with cloud platforms (
AWS
,
GCP
, or
Azure
) and their
AI-specific services
like
Amazon SageMaker
,
Google Vertex AI
, or
Azure Machine Learning
Familiarity with big-data ecosystems (
Spark
,
Hadoop
).
Practice in
CI/CD
& container orchestration (
Jenkins/GitLab CI
,
Docker
,
Kubernetes
).
Exposure to
MLOps/LLMOps
tools (
MLflow
,
Kubeflow
,
TFX
).
Experience with
Large Language Models
,
Generative AI
,
prompt engineering
, and
RAG pipelines
Hands-on experience with
vector databases
(e.g.,
Pinecone
,
FAISS
).
Experience building
AI Agents
and using frameworks like
Hugging Face Transformers
,
LangChain
or
LangGraph
Documentation skills using
PlantUML
or similar.
Benefits
Paid time off (PTO)
U.S. Holidays
Training
Udemy free Premium access
Mentored career development
Profit Sharing
$US Remuneration
Key Skills
Ranked by relevanceReady to apply?
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