We Love AI JobsData Scientist / ML Engineer (Signal Processing, Real-Time Models)
SphereJoin Sphere as a Data Scientist / ML Engineer and leverage your expertise in Signal Processing to develop real-time AI solutions for low-frequency physiological signals. You'll work in a collaborative remote environment, transitioning from consulting to hands-on model training, significantly impacting health technology.
Skills & Expertise
Key Responsibilities
Analyze signal data and define processing approaches.
Train, tune, and deploy machine learning models.
Optimize models for real-time inference and product integration.
Full Description
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