Machine Learning Engineer

21 hours ago

Taguig, National Capital Region, Philippines Seven Seven Full time $80,000 - $120,000 per year

Overview:

We are seeking a
Machine Learning Engineer
to design, develop, and deploy machine learning models and AI solutions that solve complex business problems. This role bridges the gap between data science and software engineering, ensuring models are not only accurate but also scalable and production-ready.

Key Responsibilities:

  • Collaborate with data scientists, analysts, and software engineers to understand project requirements and translate them into technical solutions.
  • Design, train, evaluate, and optimize
    machine learning models
    for various applications such as prediction, classification, recommendation, and natural language processing.
  • Prepare, clean, and analyze large datasets to improve model performance.
  • Implement scalable
    ML pipelines
    for data ingestion, model training, and deployment.
  • Integrate models into production environments and monitor their performance over time.
  • Conduct experiments, A/B testing, and model validation to ensure reliability and accuracy.
  • Research and apply new algorithms, tools, and best practices in machine learning and AI.

Qualifications:

  • Bachelor's or Master's degree in
    Computer Science, Data Science, Mathematics, or a related field
    (PhD a plus).
  • Solid programming skills in
    Python
    (experience with libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
  • Strong understanding of
    machine learning algorithms
    , statistical modeling, and data structures.
  • Experience with
    cloud platforms
    (AWS, GCP, Azure) and ML services.
  • Familiarity with
    big data tools
    (Spark, Hadoop) is a plus.
  • Strong problem-solving skills and the ability to work in a collaborative team environment.

Preferred Skills:

  • Experience with
    deep learning
    , reinforcement learning, or NLP.
  • Knowledge of
    MLOps
    tools such as MLflow, Kubeflow, or Airflow.
  • Understanding of data privacy, security, and ethical considerations in AI.

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