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No Experience Machine Learning Jobs in Foley, AL

Xcite Automotive

Automotive Photographer

Pensacola, FL · On-site

$17/hr

No prior automotive experience required! Xciting Perks! * Flexible part-time weekday hours (Monday ... Passionate about learning and working independently . * Good with time management and attention to ...

RetailData

Data Collection Representative

Mobile, AL · On-site

Field Representative - Flexible Schedules For College Students - No Experience Needed Flexible ... Opportunities for employee learning and development. Come work for an essential business! We put an ...

True North Group LLC.

Sales Agent Trainee

Mobile, AL · On-site

... Learning to close deals and manage long-term client relationships We Provide: Uncapped weekly ... No Experience, No Problem. Whether you're just out of university, switching industries, or trying ...

Alabama Credit Union

Member Experience Representative

AL · On-site

$16.42 - $24.62/hr

We create an environment rich in learning and advancement opportunities, community support ... machines, using paper (to include counting cash, sorting and filling paper items, scanning, etc ...

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How much do no experience machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for no experience machine learning in Foley, AL is $19.53, according to ZipRecruiter salary data. Most workers in this role earn between $16.88 and $21.83 per hour, depending on experience, location, and employer.

What kinds of projects or learning opportunities can I expect in a no experience machine learning role?

In a no experience machine learning role, you will often start by assisting with data preprocessing, exploring datasets, and supporting more experienced engineers on real-world projects. You may also participate in internal trainings, mentorship programs, or hands-on workshops to build up your technical skills. Collaboration is common, so expect regular team meetings and opportunities to pair-program or seek guidance from senior colleagues. Over time, as you gain proficiency, you may be assigned small-scale projects or research tasks, providing a clear pathway to take on more complex responsibilities. This supportive environment is designed to help you gradually develop expertise and advance your career in machine learning.

What are the key skills and qualifications needed to thrive in the no experience machine learning position, and why are they important?

To thrive in an entry-level machine learning role with no prior experience, you should possess a solid understanding of mathematics (especially statistics and linear algebra), basic programming knowledge (often in Python), and a willingness to learn. Familiarity with popular data science tools and frameworks such as scikit-learn, TensorFlow, or online courses and certifications in machine learning is advantageous. Curiosity, problem-solving abilities, and effective communication are soft skills that help you work collaboratively and adapt to new challenges. These attributes are important because they enable quick learning, help you contribute to team projects, and support your growth in a rapidly evolving technical field.

Can you get a machine learning job with no experience?

Entry-level machine learning roles often require some knowledge of programming, statistics, and data analysis, but many employers are willing to hire candidates with little to no experience if they demonstrate strong foundational skills and a willingness to learn. Building a portfolio through online courses, projects, and certifications can improve chances of securing such positions. Internships and apprenticeships are also common pathways for those new to the field.

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Robotics Data Pipeline Engineer - Multimodal Data

Persona AI

Pensacola, FL • On-site

$108K - $130K/yr

Other

Medical, PTO

Re-posted 4 days ago

Job description

Job Title: Robotics Data Pipeline Engineer - Multimodal Data
Department: Software
Reports To: Teleoperations Lead
Employment Type: Full-Time
Location: Houston, TX or Pensacola Fl
Who We Are
Persona AI is building humanoid robots for the most demanding environments in heavy industry - shipyards, steel mills, fabrication facilities, and offshore platforms - performing welding, grinding, maintenance, inspection, and material-handling work that is dangerous, physically demanding, and increasingly difficult to staff.
We are backed by leading strategic and financial investors and engaged with global industrial leaders across Korea, Japan, the United States, and Singapore. Korea is the center of gravity for our early commercial strategy, anchored by relationships with the world's leading shipbuilders and steelmakers. Our work spans both the robot platform itself and the systems, partners, and playbooks required to deploy it at scale.
Why Join Persona AI?
  • We offer competitive compensation, a performance-based bonus, 99% employer covered medical benefits, early-stage equity, competitive PTO, and a company-wide paid winter break between December 24th and January 2nd.
  • You'll shape technology that's redefining the possibilities of robotics and human interaction.
  • Work alongside passionate teammates who value creativity, and continuous learning.
  • Enjoy full access to advanced tools,

About the Role
As a Data Pipeline Engineer, you will architect and scale the data infrastructure that feeds our foundation models. Your primary mission is to extract, augment, and align human dexterous manipulation data from massive complex, multi-sensor and egocentric video datasets. Crucially, you will build advanced post-processing algorithms to perform deep force analysis and infer hidden states from raw data-such as processing direct force-torque outputs to quantify grasp dynamics, estimating contact forces from visual cues, extrapolating heavily occluded hand positions, or deriving 3D geometry from 2D frames. You will use spatial, temporal, and cross-modal data augmentation to multiply the value of every minute of data our teleoperation team collects.
What You Will Be Doing
  • Multimodal Data Pipelines: Architect end-to-end ingestion pipelines that take raw, unstructured recordings-egocentric video, teleoperation sessions, third-party open datasets-and produce indexed, queryable, training-ready datasets. This includes temporal segmentation of long recordings into action clips, metadata and scene-graph extraction, embedding-based retrieval, and language annotation workflows.
  • Force Analysis & Hidden State Inference: Design cross-modal validation systems that verify video, proprioception, force/haptic signals, and language annotations agree with each other-e.g., reprojecting robot state into the image plane to confirm video-state consistency, and VLM-assisted checks that instructions match observed behavior.
  • Kinematic Retargeting & Alignment: orchestrating hand-tracking, segmentation, depth estimation, 3D reconstruction, and pose-tracking modules; retargeting human demonstrations into robot trajectories; and running simulation-in-the-loop validation (kinematic feasibility, physics replay, motion-consistency filtering) so synthesized data is physically grounded, not just visually plausible.
  • Advanced Data Augmentation: Implement robust data augmentation strategies (spatial transformations, temporal scaling, synthetic viewpoints, and sensor noise injection) to expand expert trajectories and improve the robustness of our learning models.
  • Teleoperation Synchronization: unified state-action representations across differing embodiments, coordinate frames, rotation conventions, gripper/hand parameterizations, and sampling rates-with per-dimension validity masking and per-source normalization so that adding a new robot or sensor is a configuration change, not a rewrite.
  • Close the loop with data consumers: build the tooling that lets researchers query, visualize, and audit datasets (clip browsers, trajectory viewers, annotation review UIs), and turn model-failure analyses into new curation rules and targeted re-collection requests.

What We Are Looking For
  • Education: M.S., or Ph.D. in Computer Science, Data Engineering, Machine Learning, Robotics, Mechanical Engineering, or a related field.
  • Programming & ML Frameworks: Deep expertise in Python and extensive experience with PyTorch, specifically in handling custom dataloaders for multimodal datasets.
  • Force & Time-Series Data Processing: Experience analyzing and processing complex time-series data from force-torque (F/T) sensors, load cells, or tactile arrays, ensuring pristine alignment with visual frames.
  • Video Processing Expertise: Mastery of video processing pipelines and libraries (OpenCV, FFmpeg, Decord) and managing the I/O bottlenecks of terabyte-scale video datasets.
  • Solid working knowledge of 3D geometry and robotics data: coordinate frames and transforms, rotation representations, camera intrinsics/extrinsics, forward/inverse kinematics, URDF-enough to build automated checks that catch geometric inconsistencies in the data.
  • Data Augmentation: Proven ability to implement programmatic and generative data augmentation techniques for computer vision and time-series data.

Bonus Skills
  • Experience with NVIDIA's robotic software stack (Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar).
  • Familiarity with the modern perception toolbox as a user: segmentation (SAM-family), monocular depth, hand/body pose estimation (MANO/SMPL), 6-DoF object pose tracking, point tracking-you don't need to train these models, but you should be comfortable composing and evaluating them in a pipeline
  • Familiarity with distributed data processing systems (Ray, Apache Spark) for cluster computing.
  • Background in generating or utilizing synthetic robotic data via simulation (Omniverse, MuJoCo).
  • Experience integrating spatial awareness or tactile data representations (e.g., Fourier encoding) into visual pipelines.

Persona AI is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.

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