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AI​/Machine Learning Engineer

Job in Santa Monica, Los Angeles County, California, 90403, USA
Listing for: Hidonix Industries
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 100000 USD Yearly USD 90000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI / Machine Learning Engineer

We’re Hiring! AI / Machine Learning Engineer

Location: Santa Monica | On-site

Employment Type
:
Full-time

Experience Level
: 2-3 Years

Salary Range
: $90,000 – $100,000 Per year

Benefits: Comprehensive Health Coverage

About The Role

Hidonix is seeking an AI / Machine Learning Engineer to help design and implement intelligent systems that extract meaning and predictive value from computer vision and behavioral datasets. This is a junior‑level, in‑person role suited for candidates with 2–3 years of experience and a solid foundation in deep learning, embeddings, and modern neural architectures.

As a member of the AI team, the ideal candidate will work on projects that leverage CNNs, transformer models, and embedding architectures to encode and reason over pose, facial, and action‑based visual data. These systems support downstream tasks such as future action prediction, semantic matching, and similarity‑based inference.

Responsibilities
  • Design and implement machine learning pipelines that encode visual input (pose, face, object/classification) into shared embedding spaces for similarity and predictive tasks
  • Build and fine‑tune convolutional and transformer‑based neural architectures optimized for visual recognition and representation learning
  • Develop encoding and embedding techniques that allow consistent comparison across multiple data types (e.g., pose vectors, facial landmarks, class labels)
  • Apply techniques such as cosine similarity, distance metrics, and latent clustering to perform behavioral inference and action prediction
  • Contribute to model training, evaluation, and deployment workflows including data preprocessing, augmentation, hyperparameter tuning, and performance profiling
  • Collaborate closely with engineers in computer vision, embedded systems, software, and UI/UX to ensure seamless integration of AI pipelines into real‑time systems
  • Produce clean, well‑documented code and maintain version‑controlled model artifacts and experiment logs
  • Write technical documentation for models, training procedures, evaluation criteria, and system integration
Qualifications
  • Bachelor’s or Master’s degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or a closely related discipline
  • 2–3 years of experience in machine learning roles through internships, academic labs, or early career positions
  • Strong understanding of:
  • Convolutional Neural Networks (CNNs) for image and video‑based tasks
  • Transformer architectures and their applications in vision or multimodal learning
  • Embedding systems and vector space modeling for semantic and similarity‑based tasks
  • Encoding mechanisms and dimensionality reduction techniques for latent representation
  • Proficiency in Python and deep learning frameworks such as PyTorch or Tensor Flow
  • Familiarity with pose estimation, facial recognition, or classification models (e.g., Open Pose, Media Pipe, Face Net, Res Net variants)
  • Experience training models with structured and unstructured visual datasets
  • Exposure to techniques like cosine similarity, triplet loss, contrastive learning, or temporal prediction modeling
  • Strong computer science fundamentals, including data structures, algorithms, and software design patterns
  • Comfort working in Linux‑based development environments and version control systems (Git)
  • A collaborative mindset, with excellent communication skills and a willingness to learn across domains
Bonus (Nice‑to‑Have)
  • Experience integrating vision‑based AI models into embedded or robotics systems
  • Familiarity with ONNX or Tensor

    RT for model optimization and deployment
  • Background in sequence modeling, recurrent architectures, or video‑based action recognition
  • Exposure to multimodal AI systems that blend image, pose, and metadata representations
  • Familiarity with techniques like CLIP, DINO, or self‑supervised representation learning
  • Experience with MLOps or training orchestration tools such as MLflow, Weights & Biases, or DVC
What we offer
  • Full Health Coverage
  • A collaborative and intellectually driven team environment
  • Flexible PTO
Equal Opportunity & Application Policy

We are an equal opportunity employer and welcome applicants from all backgrounds.

Please note:
  • We are currently not accepting applications from third‑party recruiting services
  • We are not offering visa sponsorship for this role at this time. Applicants must be U.S. citizens or permanent residents (Green Card holders)
  • Candidates must reside within a commutable distance of Santa Monica, California.
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