Senior AI/ML Engineer
5 days ago
About Us
Beatly.AI
is a fast-growing artificial intelligence company focused on building intelligent, data-driven solutions that make a real-world impact. We develop cutting-edge technologies that enhance decision-making and efficiency across critical domains. If you're passionate about creating meaningful AI products and thrive in a collaborative, innovation-driven environment, we'd love to have you on our team.
About the Role
We are looking for a Senior AI/ML Engineer
with strong hands-on experience in
Convolutional Neural Networks (CNNs)
and traditional deep learning techniques. The role involves designing, developing, and deploying machine learning models for pattern recognition and time-series or image-based applications.
You'll work closely with data engineers, software developers, and domain experts to build reliable and scalable AI systems from research prototypes to production-ready solutions.
Key Responsibilities
• Design and implement
deep learning models (CNN, RNN, LSTM)
for data classification, segmentation, or prediction tasks.
• Develop robust
data preprocessing and feature extraction
pipelines for structured and unstructured datasets.
• Optimize model architecture, training, and inference for performance and scalability.
• Analyze and interpret model outputs, ensuring reliability and explainability.
• Collaborate with cross-functional teams to integrate AI models into production environments.
• Conduct model evaluation using statistical and domain-relevant performance metrics.
• Mentor junior engineers and contribute to design discussions and technical reviews.
Required Skills & Experience
•
4–10 years
of experience in applied machine learning or deep learning development.
• Proven expertise in
CNN-based model design
for image or signal data.
• Proficiency in
Python
and major deep learning frameworks such as
TensorFlow
,
PyTorch
, or
Keras
.
• Strong understanding of
signal processing
, data normalization, and augmentation techniques.
• Familiarity with
model optimization
, quantization, and deployment practices.
• Experience with
version control (Git)
and
ML Ops
tools (Docker, Kubernetes, or cloud ML platforms).
• Solid grounding in
mathematics, statistics, and algorithm design
.
Preferred Qualifications
• Master's or Ph.D. in Computer Science, Electrical Engineering, or related field.
• Experience with
time-series data analysis
or
real-time inference systems
.
• Background in
end-to-end AI pipeline development
— from data collection to deployment.
• Exposure to
regulatory or safety-critical environments
is a plus.
What We Offer
• Opportunity to build and deploy cutting-edge AI systems with real-world impact.
• Collaborative and technically strong R&D environment.
• Competitive compensation, flexibility, and professional development opportunities.
• Access to diverse datasets and advanced computing infrastructure.
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