Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 40 hours ago

Machine Learning Engineer - Mid

SOSi332 open roles

Where
Huntsville, AL, United States
Work mode
On site
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowMachine Learning Engineer - MidSOSi · Huntsville, AL, United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on SOSi's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.6% of postings close within 7 days. Measured by our own scanner across the market. SOSi postings stay open a median of 35 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.7%3 days
  3. 13.6%7 days
  4. 21.9%14 days
  5. 36.9%30 days
  6. 59.0%60 days
This job: posted 40 hours ago

SOSi median: 35 days open

The posting

Company Description

Founded in 1989 and headquartered in Reston, Virginia, SOSi is a private defense and government solutions business specializing in advanced technology systems and mission support. Its capabilities include data science, software development, network engineering, intelligence, surveillance, and reconnaissance (ISR), and logistics.

Job Description

SOSi is seeking a Mid-Level Machine Learning Engineer to support the development, integration, and deployment of machine learning capabilities for a government customer in Huntsville, Alabama.

The selected candidate will contribute to an MLOps environment supporting national security missions and large-scale analytical workloads. The position focuses on transforming machine learning prototypes into reliable, maintainable, and production-ready capabilities.

The ideal candidate has practical experience developing machine learning models, writing production-quality Python, and integrating models into established software systems. Candidates should understand the full machine learning lifecycle, including data preparation, experimentation, evaluation, deployment, monitoring, and continuous improvement.

The engineer will work alongside data scientists, data engineers, and software developers in an Agile environment to deliver solutions aligned with mission requirements.

The team works with technologies including Python, PyTorch, scikit-learn, MLflow, PostgreSQL, Docker, Linux, GitLab, Jupyter Notebooks, and supporting MLOps infrastructure.

Essential Job Duties

Machine Learning Development

  • Develop, train, evaluate, and improve machine learning models for operational applications.
  • Apply supervised and unsupervised learning techniques to structured and unstructured datasets.
  • Perform feature engineering, data preprocessing, and dataset validation.
  • Select appropriate algorithms and evaluation metrics based on project requirements.
  • Conduct experiments, compare model performance, and document technical findings.
  • Identify and address model performance issues, including overfitting, data leakage, and prediction errors.

Production ML Engineering

  • Convert research prototypes and notebooks into maintainable Python modules and services.
  • Integrate trained models into existing applications, APIs, and processing workflows.
  • Package and deploy model inference services using containerized environments.
  • Implement consistent model loading, configuration management, and error handling.
  • Support model versioning, experiment tracking, and reproducible deployments.
  • Investigate and resolve model inference, integration, and performance issues.
  • Contribute to automated model validation and deployment workflows.

Software Development and Quality Assurance

  • Write clean, modular, testable, and maintainable Python code.
  • Develop unit tests for preprocessing, feature engineering, and model-related functionality.
  • Develop integration tests validating model interactions with dependent systems.
  • Implement smoke tests confirming deployed services operate as expected.
  • Participate in peer code reviews and address identified defects.
  • Use Git-based development workflows and established CI/CD practices.
  • Maintain technical documentation covering implementation, testing, and operational procedures.

Data Integration and MLOps

  • Collaborate with data engineers to establish reliable training and inference datasets.
  • Implement validation checks for dataset quality, schema consistency, and missing values.
  • Work with PostgreSQL and other approved data sources.
  • Use MLflow or comparable tools to manage experiments and model artifacts.
  • Support model registry workflows, version promotion, and rollback procedures.
  • Monitor model behavior, resource utilization, and inference performance.
  • Identify data drift, performance degradation, and operational anomalies.
  • Support reproducible model training and deployment processes.

Collaboration and Delivery

  • Complete assigned development tasks within agreed sprint objectives.
  • Communicate implementation progress, technical blockers, and delivery risks.
  • Provide realistic estimates for assigned engineering efforts.
  • Coordinate interface requirements with data engineering and software development teams.
  • Follow established architecture, coding, testing, and documentation standards.
  • Identify proposed scope changes before implementing unapproved functionality.
  • Participate in technical discussions, planning sessions, and code reviews.

Qualifications

Minimum Requirements

  • Active Top Secret clearance with SCI eligibility.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related quantitative discipline.
  • 3–5 years of relevant experience in machine learning engineering, software development, or applied data science.
  • Proficiency in Python and common machine learning libraries.
  • Practical experience training, evaluating, and deploying machine learning models.
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Experience using SQL and relational databases.
  • Working knowledge of Linux development environments and command-line tools.
  • Experience with Git, collaborative development, and pull request workflows.
  • Familiarity with Docker and containerized application deployment.
  • Understanding of automated testing, including unit and integration testing.
  • Knowledge of REST APIs and integration between software components.
  • Understanding of CI/CD principles and Agile development methodologies.
  • Ability to independently implement, troubleshoot, and deliver assigned engineering tasks.

Preferred Qualifications

  • Experience deploying and maintaining machine learning models in production.
  • Experience with MLflow or similar experiment tracking and model registry platforms.
  • Familiarity with Triton Inference Server or comparable inference serving platforms.
  • Experience developing computer vision, NLP, classification, or anomaly detection solutions.
  • Experience integrating machine learning models into ETL/ELT pipelines.
  • Familiarity with Apache Airflow or similar workflow orchestration tools.
  • Experience with PostgreSQL, large-scale datasets, or distributed processing.
  • Understanding of model monitoring, data drift, reproducibility, and rollback strategies.
  • Familiarity with GitLab CI/CD, automated validation, and container registries.
  • Experience developing solutions in restricted, offline, or on-premises computing environments.
  • Experience supporting DoD or Intelligence Community missions.
  • Exposure to high-performance computing and multi-INT analytical workloads.

Additional Information

Work Environment

  • Office-based position in Huntsville, Alabama.
  • Collaboration with multidisciplinary engineering and government stakeholder teams.
  • Work involving mission-sensitive data and secure computing environments.
  • Occasional remote work or travel may be available based on program requirements.

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against SOSi's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on SOSi's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    SOSi's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.