Jecona
We are partnering with an org that is building intelligent systems that transform how organizations leverage data and automation. Our team works at the intersection of machine learning, engineering, and product to deliver scalable, real-world AI solutions.
The Role We are looking for a
Machine Learning Engineer
to design, build, and deploy machine learning models where you will work closely with software engineers, product managers, and data stakeholders to take models from experimentation to production.
They are opening up a new office in the East Bay and the role will be onsite from East Bay. Salary for this is 150k - 250k, depending on experience.
What You’ll Do
Design, train, and deploy machine learning models for real-world applications
Build scalable ML pipelines for data processing, training, evaluation, and inference
Collaborate with engineering teams to integrate models into production systems
Optimize model performance, reliability, and scalability
Monitor deployed models and iterate based on performance and feedback
Stay current with advances in machine learning, AI, and data science
What We’re Looking For
1-7 years of experience in machine learning, data science, or applied AI
Strong proficiency in
Python
and common ML libraries (PyTorch, TensorFlow, scikit-learn)
Experience working with structured and unstructured data
Solid understanding of ML fundamentals (supervised/unsupervised learning, evaluation metrics, feature engineering)
Experience deploying models into production environments
Familiarity with cloud platforms (AWS, GCP, or Azure)
Nice to Have
Experience with NLP, computer vision, or large language models
Knowledge of MLOps tools (MLflow, Airflow, Kubeflow, SageMaker)
Experience with data pipelines and distributed systems (Spark, Kafka)
Startup or fast-paced environment experience
Seniority level Mid-Senior level
Employment type Full-time
Job function Business Consulting and Services
#J-18808-Ljbffr
The Role We are looking for a
Machine Learning Engineer
to design, build, and deploy machine learning models where you will work closely with software engineers, product managers, and data stakeholders to take models from experimentation to production.
They are opening up a new office in the East Bay and the role will be onsite from East Bay. Salary for this is 150k - 250k, depending on experience.
What You’ll Do
Design, train, and deploy machine learning models for real-world applications
Build scalable ML pipelines for data processing, training, evaluation, and inference
Collaborate with engineering teams to integrate models into production systems
Optimize model performance, reliability, and scalability
Monitor deployed models and iterate based on performance and feedback
Stay current with advances in machine learning, AI, and data science
What We’re Looking For
1-7 years of experience in machine learning, data science, or applied AI
Strong proficiency in
Python
and common ML libraries (PyTorch, TensorFlow, scikit-learn)
Experience working with structured and unstructured data
Solid understanding of ML fundamentals (supervised/unsupervised learning, evaluation metrics, feature engineering)
Experience deploying models into production environments
Familiarity with cloud platforms (AWS, GCP, or Azure)
Nice to Have
Experience with NLP, computer vision, or large language models
Knowledge of MLOps tools (MLflow, Airflow, Kubeflow, SageMaker)
Experience with data pipelines and distributed systems (Spark, Kafka)
Startup or fast-paced environment experience
Seniority level Mid-Senior level
Employment type Full-time
Job function Business Consulting and Services
#J-18808-Ljbffr