Data Scientist / ML Engineer (Signal Processing, Real-Time Models)

Position:

Data Scientist / Machine Learning Engineer

Client:

AI-Driven HealthTech / Signal Analytics Company

Engagement Type:

Consulting → Potential Phase 3 Implementation

Location:

Remote

Level:

Middle

We are looking for a

Data Scientist / ML Engineer with strong Signal Processing expertise

to support

early product consulting

and later

Phase 3 model training and optimization

.

Initially, the specialist will

consult on signal processing approach, model architecture, and data preparation strategy

.

At

Phase 3 of product development

, the same specialist will

train, tune, and deploy real-time machine learning models

.

The product focuses on

low-frequency physiological signals

such as

ECG, brain waves, and other biosignals

, requiring

signal filtering, transformation, and feature engineering

for real-time AI solutions.

Key Responsibilities

Phase 1-2: Consulting & Architecture

• Analyze available signal data and product requirements

• Define signal processing and filtering approaches

• Recommend model architecture and ML approach

• Define feature extraction strategy

• Advise on real-time processing pipeline

• Provide technical guidance on model feasibility and performance

Phase 3: Model Training & Implementation

• Process low-frequency physiological signals (ECG, brain waves, biosignals)

• Apply signal filtering and mathematical transformations

• Build feature extraction pipelines

• Train and tune machine learning models

• Optimize models for real-time inference

• Support integration into production environment

• Improve model accuracy and performance

Required Experience

• 3+ years as Data Scientist / ML Engineer

• Strong experience with Signal Processing

• Experience working with ECG, EEG, brain waves, or similar signals

• Experience filtering low-frequency signals (non high-frequency focus)

• Hands-on experience with:

• Signal filtering

• Noise reduction

• Signal transformation

• Feature engineering from signals

• Experience building real-time machine learning solutions

• Python skills (NumPy, SciPy, Pandas, Scikit-learn)

• Experience training and tuning machine learning models

Nice to Have

• Experience with biomedical signals

• Experience with time-series modeling

• Experience with real-time inference pipelines

• Familiarity with deep learning frameworks (PyTorch, TensorFlow)

• Experience working with edge devices or streaming data

Technical Skills

• Signal Processing

• Time-Series Analysis

• Real-Time Machine Learning

• Python (NumPy, SciPy, Pandas)

• Model Training & Optimization

• Feature Engineering

• Data Filtering & Transformation

• Statistical Modeling

Engagement Model

• Phase 1–2: Consulting / Advisory

• Phase 3: Model Training & Implementation

• Mid-level hands-on specialist

• Real-time signal-based AI product