Talantix.io
Remote Position•11.03.26
AI SCORE 8.5

Senior Data Engineer /​ Machine Learning Engineer - Remote

$120K–$150K/year
RemoteAI/Big Data
Python•SQL•Apache Spark•Machine Learning•Deep Learning•Natural Language Processing•MLOps•PyTorch

About the Role

We are seeking a Senior Data Engineer / Machine Learning Engineer to join our team remotely. In this role, you will leverage your expertise in data engineering and machine learning to build robust data pipelines and develop predictive models that drive business insights. As a Senior Data Engineer / Machine Learning Engineer remote position, you will collaborate with cross-functional teams to tackle complex data challenges and contribute to innovative solutions.

What You'll Do

  • Design and implement scalable data pipelines for processing large datasets.
  • Develop machine learning models to enhance predictive capabilities.
  • Collaborate with data scientists and analysts to understand data requirements.
  • Optimize data workflows and ensure data quality and integrity.
  • Engage with diverse data sources, including geospatial data and time-series data.

Requirements

  • 5+ years of experience as a Data Engineer or Machine Learning Engineer.
  • Proficiency in Python and SQL for data manipulation and analysis.
  • Experience with data processing frameworks such as Apache Spark.
  • Strong understanding of machine learning algorithms and techniques.
  • Familiarity with MLOps practices and tools.

Nice to Have

  • Experience with deep learning frameworks like PyTorch or TensorFlow.
  • Knowledge of natural language processing (NLP) techniques.
  • Familiarity with cloud platforms (AWS, Azure, GCP).

What We Offer

  • Competitive salary based on experience.
  • Remote work flexibility with a supportive team environment.
  • Opportunities for continuous learning and professional development.
  • Engagement with world-class developers and designers.
  • Challenging projects that involve diverse data sources.
Why This Job8.5 of 10

This role offers a unique opportunity for experienced data engineers and machine learning engineers to work remotely on challenging projects with a competitive salary.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

→

Proficient in Python and SQL, with hands-on experience in Apache Spark for large-scale data processing, allowing for efficient data pipeline creation and maintenance.

→

Strong understanding of MLOps practices and tools, such as MLflow or Kubeflow, to streamline the deployment and management of machine learning models in production environments.

→

Experience with deep learning frameworks, particularly PyTorch, and knowledge of Natural Language Processing techniques, enabling the development of sophisticated models for text-based data.

Learning Resources

→Python for Data Science Handbookguide
→Introduction to Apache Spark for Data Sciencecourse
→Deep Learning with PyTorch: A 60 Minute Blitzarticle

Career Path

Senior Data Engineer / Machine Learning Engineer(Now)→Lead Data Engineer / Machine Learning Architect(2-4 years)→Director of Data Science / AI Solutions(5-7 years)

Market Overview

Market Size 2024
$20B
Annual Growth
22.5%
AI Adoption
65%
Investment
+150%
Labour Demand
+30%
Avg Salary
$130K

Skills & Requirements

Required
PythonSQLApache Spark
Growing in Demand
Data Visualization (e.g., Tableau, Power BI)Cloud Computing (e.g., AWS, Azure)Big Data Technologies (e.g., Hadoop, Kafka)
Declining
R ProgrammingHadoop MapReduce

Domain Trends

Increased Demand for MLOps
With a 40% rise in companies adopting MLOps practices, there is a growing need for engineers who can streamline the deployment and monitoring of machine learning models.
Shift Towards Real-time Data Processing
Over 55% of organizations are transitioning to real-time data processing architectures, emphasizing the importance of skills in Apache Spark and streaming technologies.
Focus on Ethical AI
Around 70% of tech companies are prioritizing ethical AI practices, leading to a demand for engineers who can implement responsible AI frameworks and algorithms.

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