What are the responsibilities and job description for the Machine Learning Engineer position at Harnham?
Machine Learning Engineer
AdTech
Remote
$175,000 - $205,000 USD/yr bonus
Harnham is partnering with an ad technology firm that provides services to help advertisers to optimize their ad campaigns. Their tools are used to help maximize engagement and conversion of ads. This firm is looking for a Machine Learning Engineer to join their Data Science team. This role is critical for developing and implementing advanced machine learning models that operate at scale in a high-performance, data-driven environment.
If you thrive in complex, data-driven settings and are eager to contribute to the development of innovative machine learning solutions that solve real-world business challenge. This role could be for you.
THE ROLE
The Machine Learning Engineer will work closely with cross-functional teams of data scientists, engineers, and business stakeholders to deliver ML solutions that address complex, high-impact challenges. This position requires expertise in deploying models, using AWS, GCP, or Azure. This role requires experience with for high-throughput and low-latency settings.
RESPONSIBILITIES
- Collaborate on designing and implementing machine learning models to tackle complex business needs in areas like recommendation systems, predictive analytics, and natural language processing.
- Deploy models into cloud environments (AWS, GCP, Azure) and manage the pipeline using Docker and Kubernetes.
- Ensure models are production-ready, scalable, and reliable, working alongside engineering teams to maintain performance standards.
- Monitor model efficacy in live environments, troubleshooting and optimizing as needed.
- Contribute to ongoing research efforts and stay abreast of advancements in machine learning to continuously improve capabilities.
YOUR SKILLS AND EXPERIENCE
- Proven commercial experience in machine learning engineering, with proficiency in languages such as Python, SQL, or Java.
- Proven expertise in end-to-end model development, including inception, deployment, and automated retraining of advanced models (e.g., Contextual Bandits, Deep Neural Networks).
- Advanced degree (Master's or Ph.D.) in Statistics, Computer Science, or a related field is preferred.
- Experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and machine learning tools (Databricks, MLFlow, etc.).
- Strong analytical and problem-solving skills, with the ability to communicate complex concepts to non-technical stakeholders.
BENEFITS
You could earn $175,000 - $205,000 USD/yr based on experience bonus, along with a remote working environment.
HOW TO APPLY
For those with a strong background in machine learning who are looking to make a significant impact within a fast-paced, collaborative environment, we encourage you to reach out for more details.
Please register your interest by sending your resume to Virginia via the Apply link on this page.
KEYWORDS
Machine Learning | Model Deployment | Recommendation | NLP | Contextual Bandit | Deep Neural Networks | Python | SQL | AWS | GCP | Azure | Docker | Kubernetes | MLflow | Kubeflow | TensorFlow | Pytorch
Salary : $175,000 - $205,000
